2003•Transactions of the Atomic Energy Society of JapanOpen access

Quantification of a Decision-making Failure Probability of the Accident Management Using Cognitive Analysis Model

Yoshitaka Yoshida, Masanori Ohtani, Yushi Fujita

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Abstract

In a nuclear power plant, much knowledge on severe accidents has been acquired through PSA, and accident management (AM) guidelines are prepared by incorporating that knowledge.In PSA, it is necessary to evaluate the effectiveness of AM using the decision-making failure probability (DFP) of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipment.However, to date there has been no suitable quantification method for PSA to obtain DFP.In this study, we developed a new method for DFP quantification of an emergency organization using a cognitive analysis model, and tried to apply it to S2DC and TMLF sequence of a typical plant.As a result: (1) The methods enabled to DFP quantification appropriate to level 1.5PSA by choosing the suitable value of a basic failure probability and an error factor.(2) The DFPs of six AMs appeared to be in the range of 0.23 to 0.41 (screening method) and in the range of 0.10 to 0.19 (detailed method), and the DFP decreased about 50% as a result of sensitivity analysis of the conservative assumption.(3) The screening method was more conservative than the detailed method, and it was shown to satisfy the screening performance required by PSA.

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In a nuclear power plant, much knowledge on severe accidents has been acquired through PSA, and accident management (AM) guidelines are prepared by incorporating that knowledge.In PSA, it is necessary to evaluate the effectiveness of AM using the decision-making failure probability (DFP) of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipment.However, to date there has been no suitable quantification method for PSA to obtain DFP.In this study, we developed a new method for DFP quantification of an emergency organization using a cognitive analysis model, and tried to apply it to S2DC and TMLF sequence of a typical plant.As a result: (1) The methods enabled to DFP quantification appropriate to level 1.5PSA by choosing the suitable value of a basic failure probability and an error factor.(2) The DFPs of six AMs appeared to be in the range of 0.23 to 0.41 (screening method) and in the range of 0.10 to 0.19 (detailed method), and the DFP decreased about 50% as a result of sensitivity analysis of the conservative assumption.(3) The screening method was more conservative than the detailed method, and it was shown to satisfy the screening performance required by PSA.

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Available abstract

In a nuclear power plant, much knowledge on severe accidents has been acquired through PSA, and accident management (AM) guidelines are prepared by incorporating that knowledge.In PSA, it is necessary to evaluate the effectiveness of AM using the decision-making failure probability (DFP) of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipment.However, to date there has been no suitable quantification method for PSA to obtain DFP.In this study, we developed a new method for DFP quantification of an emergency organization using a cognitive analysis model, and tried to apply it to S2DC and TMLF sequence of a typical plant.As a result: (1) The methods enabled to DFP quantification appropriate to level 1.5PSA by choosing the suitable value of a basic failure probability and an error factor.(2) The DFPs of six AMs appeared to be in the range of 0.23 to 0.41 (screening method) and in the range of 0.10 to 0.19 (detailed method), and the DFP decreased about 50% as a result of sensitivity analysis of the conservative assumption.(3) The screening method was more conservative than the detailed method, and it was shown to satisfy the screening performance required by PSA.

Key concepts: Reliability (semiconductor), Reliability engineering, Computer science, Range (aeronautics), Nuclear power plant, Cognition, Risk analysis (engineering), Power (physics)

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