Experimental investigation on the thermal performance of multi-stream plate-fin heat exchanger based on genetic algorithm layer pattern design

Abstract

Efficient approaches are imperative for the design of the layer pattern of multi-stream plate-fin heat exchangers (MPFHE) to obtain enhanced thermal performance. This paper presents few layer pattern criterion models to determine optimal stacking pattern. These models were developed by employing a genetic algorithm with binary chromosome ring representing alternatively placed hot and cold layer fluid streams. The method of dual fitness alternating optimization functions was used for conducting local heat energy balance and single layer thermal load difference. The zigzag pattern weighted deviation of the cumulative heat load σ was evaluated for the layer pattern. An experimental study was conducted on layer pattern to test the optimality of the stacking pattern. The experimental data and HTFS MUSE simulation results were found to be in agreement. The optimized results showed that the smallest value of σ was in the range of 0.05–0.20, and that the average thermal efficiency of exchanger was higher than 98%. From these results it was concluded that the performance of MPFHE in relation to heat transfer and fluid flow was effectively improved by the optimization design of the genetic algorithm (GA) layer pattern.