Abstract
The regulation of nuclear power plant (NPP) is evolving in a direction to harmonize probabilistic safety criteria in the near future. The utilities will not only have to demonstrate that they are operating below a target risk level but also to demonstrate that the unavailability of some of the critical safety systems are below a specified level. In order to satisfy the Technical Specification and Maintenance (TS&M) requirements in a cost effective manner multi-objective optimization of TS&M requirements is of profound interest. The constrained multi-objective optimization of the TS&M requirements of a nuclear power plant (NPP) based on risk and cost gives the pareto-optimal solutions, from which the utility can pick suitable decision variables. The paper presents a multi objective genetic algorithm (GA) technique to investigate a trade-off between risk and cost both at the system and the plant level for Loss of Coolant Accident (LOCA) and Main Steam Line Break (MSLB) as initiating events in a NPP.
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