skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Developing a fuzzy rule based cognitive map for total system safety assessment

Abstract

Total System Performance Assessment, TSPA, for radioactive waste disposal is a multi and interdisciplinary task that is characterized by complex interactions between parameters and processes; lack of data; and ignorance regarding natural processes and conditions. The vagueness in the determination of ranges of values of parameters and identification of interacting processes pose further difficulties to the analysts with regard to the establishment of the relations between processes and parameters. More specifically the vagueness makes uncertainty propagation and sensitivity analysis challenging to analyze. To cope with these difficulties experts often use simplifications and linguistic terms to express their state of knowledge about a certain situation. For example, experts use terms such as 'low pH', 'very unlikely', etc to describe their perception about natural processes or conditions. In this work we propose the use of Fuzzy Cognitive Maps, FCM, for representation of interrelation between processes and parameters as well as to promote a better understanding of the system performance. Fuzzy cognitive maps are suited for the case where the causal relations are not clearly defined and, therefore, can not be represented by crisp values. In other words, instead of representing the quality of the interactions by crisp values, they are assigned degreesmore » of truth. For example, we can assign values to the effect of one process on another such that (+) 1 corresponds to positive, (-) 1 to negative and 0 to neutral effects respectively. In this case the effect of a process A, on a process, B, can be depicted as function of the membership to the fuzzy set 'causal effect' of the cause process to the target one. One of the main advantages of this methodology would be that it allows one to aggregate the linguistic expressions as descriptions of processes. For example, a process can be known to have a 'very strong' positive effect on another one, or using fuzzy sets terminology the effect is 'around (+) 1' with degree of membership {mu}=0.9. As another example, a 'moderate' negative effect can be represented as 'around (-) 1' with degree of membership {mu}=0.6 to the set '(-) 1'. Such a methodology can be an important tool for enhancing transparency in the TSPA process by allowing discussions between experts from different fields of research, for example by adding new 'what if' analysis, and, therefore, for confidence building. (authors)« less

Authors:
 [1];  [2]
  1. CNEN National Nuclear Energy Commission (Brazil)
  2. Brookhaven National Laboratory (United States)
Publication Date:
Research Org.:
American Society of Mechanical Engineers (ASME), Three Park Avenue, New York, NY 10016-5990 (United States); Technological Institute of the Royal Flemish Society of Engineers (TI-K VIV), Het Ingenieurshuis, Desguinlei 214, 2018 Antwerp (Belgium); Belgian Nuclear Society (BNS) - ASBL-VZW, c/o SCK-CEN, Avenue Hermann Debrouxlaan, 40 - B-1160 Brussels (Belgium)
OSTI Identifier:
21156292
Resource Type:
Conference
Resource Relation:
Conference: ICEM'07: 11. International Conference on Environmental Remediation and Radioactive Waste Management, Bruges (Belgium), 2-6 Sep 2007; Other Information: Country of input: France; 6 refs.; Proceedings may be ordered from ASME Order Department, 22 Law Drive, P.O. Box 2300, Fairfield, NJ 07007-2300 (United States)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; BUILDINGS; FUZZY LOGIC; OPACITY; PERFORMANCE; PH VALUE; RADIOACTIVE WASTE DISPOSAL; RISK ASSESSMENT; SENSITIVITY ANALYSIS

Citation Formats

Lemos, Francisco Luiz de, and Sullivan, Terry. Developing a fuzzy rule based cognitive map for total system safety assessment. United States: N. p., 2007. Web.
Lemos, Francisco Luiz de, & Sullivan, Terry. Developing a fuzzy rule based cognitive map for total system safety assessment. United States.
Lemos, Francisco Luiz de, and Sullivan, Terry. Sun . "Developing a fuzzy rule based cognitive map for total system safety assessment". United States.
@article{osti_21156292,
title = {Developing a fuzzy rule based cognitive map for total system safety assessment},
author = {Lemos, Francisco Luiz de and Sullivan, Terry},
abstractNote = {Total System Performance Assessment, TSPA, for radioactive waste disposal is a multi and interdisciplinary task that is characterized by complex interactions between parameters and processes; lack of data; and ignorance regarding natural processes and conditions. The vagueness in the determination of ranges of values of parameters and identification of interacting processes pose further difficulties to the analysts with regard to the establishment of the relations between processes and parameters. More specifically the vagueness makes uncertainty propagation and sensitivity analysis challenging to analyze. To cope with these difficulties experts often use simplifications and linguistic terms to express their state of knowledge about a certain situation. For example, experts use terms such as 'low pH', 'very unlikely', etc to describe their perception about natural processes or conditions. In this work we propose the use of Fuzzy Cognitive Maps, FCM, for representation of interrelation between processes and parameters as well as to promote a better understanding of the system performance. Fuzzy cognitive maps are suited for the case where the causal relations are not clearly defined and, therefore, can not be represented by crisp values. In other words, instead of representing the quality of the interactions by crisp values, they are assigned degrees of truth. For example, we can assign values to the effect of one process on another such that (+) 1 corresponds to positive, (-) 1 to negative and 0 to neutral effects respectively. In this case the effect of a process A, on a process, B, can be depicted as function of the membership to the fuzzy set 'causal effect' of the cause process to the target one. One of the main advantages of this methodology would be that it allows one to aggregate the linguistic expressions as descriptions of processes. For example, a process can be known to have a 'very strong' positive effect on another one, or using fuzzy sets terminology the effect is 'around (+) 1' with degree of membership {mu}=0.9. As another example, a 'moderate' negative effect can be represented as 'around (-) 1' with degree of membership {mu}=0.6 to the set '(-) 1'. Such a methodology can be an important tool for enhancing transparency in the TSPA process by allowing discussions between experts from different fields of research, for example by adding new 'what if' analysis, and, therefore, for confidence building. (authors)},
doi = {},
url = {https://www.osti.gov/biblio/21156292}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2007},
month = {7}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: