Design and Development of Genetic Algorithm for Test Interval Optimization of Safety Critical System for a Nuclear Power Plant

With the increase in Nuclear Power Plant (NPP) operating experience, the importance of effectively scheduling the maintenance activities has been recognized as it decreases the testing and maintenance costs without compromising the plant safety. Surveillance Tests are vital for safety critical systems of nuclear plants that need regular maintenance for ensuring reliable functioning. Deciding the value of Surveillance Test Interval forms 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. 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. KeywordsGenetic Algorithm; Nuclear Power Plants; Safety Grade Decay Heat Removal System; Simple Genetic Algorithm; Steady State Genetic Algorithm; Prototype Fast Breeder Reactor