Multi-objective shape optimization of a heat exchanger using parallel genetic algorithms

We perform in this paper a multi-objective design optimization concerning the blade shape of a heat exchanger, considering the coupled solution of the flow/heat transfer processes. For this, a genetic algorithm is used. The aim of the procedure is to find the geometry most favorable to simultaneously maximize heat exchange while obtaining a minimum pressure loss. An in-house computer package, called OPAL, performs the optimization process in a fully automatic manner. It calls the pre-processor to generate the computational geometry as well as the mesh, it then performs the numerical simulation of the coupled fluid flow/heat transfer problem using Fluent, calculates the output parameters, and iterates the procedure. The genetic algorithm relies on a relatively large number of simulations, which may result in a considerable computational effort, depending on the configuration. The procedure can thus be performed in parallel on a Linux PC cluster to reduce user waiting time. A nearly optimal speed-up is obtained for the present configuration.