Performing multiobjective optimization on perforated plate matrix heat exchanger surfaces using genetic algorithm

Matrix Heat Exchanger is having wide spread applications in cryogenics and aerospace, where high effectiveness and compactness is essential. This can be achieved by providing high thermal conductive plates and low thermal conductive spacers alternately. These perforated plate matrix heat exchangers have near to 100% efficiency due to low longitudinal heat transfer. The heat transfer and flow friction characteristics of a perforated plate matrix heat exchanger can be represented using Colburn factor and friction factor. In this paper, dimensionless parameters like Reynolds number (Re), porosity (p), perforation perimeter factor (P f), plate thickness to pore diameter ratio (l/d) and spacer thickness to plate thickness ratio (s/l) have been optimized for maximum Colburn factor and minimum friction factor using genetic algorithm. Two algorithms, one for single objective and the other for multi-objective problems, which are believed to be more efficient, are described. The algorithms coded with MATLAB, is used to perform multi-objective optimization on perforated plate matrix heat exchanger surfaces. The results show promising results