Neural network and genetic algorithms for optimizing the plate element of Egyptian research reactor problems

The Second Egyptian Research Reactor ET-RR-2 went critical on the 27th of November 1997. The National Center of Nuclear Safety and radiation Control ‘NCNSRC’ has the responsibility of the evaluation and the assessment of the safety of this reactor. Multi-objective optimization is a powerful tool for resolving conflicting objectives in engineering design and numerous other fields. The purpose of this paper is to present an approach to the optimization of the fuel element plate, which is designed with a view to improve reliability and lifetime and it is one of the most important elements during the shut down. In this paper, we present a conceptual design approach for fuel element plate, in conjunction with a genetic algorithm and comparing with neural networks to obtain a fuel plate that maximizes a fitness value to optimize the safety design of the fuel plate.