Optimization Design of Fintube of Air Cooler Geometry Using Genetic Algorithm

Abstract

In the conceptual design of a sodium-cooled fast reactor system, structural integrity evaluation for various operating conditions is carried out for many components. The application of the optimization design is examined to find the shape with high design feasibility efficiently and at low cost. In this study, using a fin-tube heat transfer of an air heat exchanger (AHX) as an example, the Pareto solution which satisfies maximization of heat transfer area, minimization of pressure drops, and minimization of thermal stress was obtained by the multi-objective genetic algorithm NSGA-II. By comparison with the Monte Carlo calculation (MCS), it was confirmed that the Pareto solution by the multi-objective genetic algorithm NSGA-II corresponded to the boundary within the range of possible solutions. And it was possible to obtain the Pareto solution in a short time by using multi-objective genetic algorithm NSGA-II.