Genetic algorithm based risk-cost analysis of Neutron Flux Monitoring System for Prototype Fast Breeder Reactor

The risk-cost analysis for safety critical systems of nuclear power plants (NPPs) are very useful in safe, economical and effective design and operation of such plants. The issue of risk effectiveness versus associated costs is an optimization problem where two separate cases can be considered. First one is the cost minimization while the performance or unavailability is constrained to be at a given level. The second case is the maximization of availability or performance for the given cost level. In this study a maintenance risk-cost model is established for a safety critical system i.e. triplicated neutronic channels of a 500 MWe fast breeder nuclear reactor and a genetic algorithm (GA) is applied to solve the model to get the global optimized maintenance strategy. The results obtained are validated with the reference study results.