A new optimal design approach for plate-fin heat exchangers by evolutionary computation

Abstract

Plate-fin heat exchangers (PFHEs) are extensively implemented in practical applications due to their superior compactness and comparatively good heat transfer rate. Nevertheless, the desired high performance and relatively low weight is connected to high pressure drops that consequently result in additional costs. Hence, the design task of PFHEs for industrial applications is an intricate process. To overcome the existing difficulties, this research presents a novel evolutionary-based approach for design optimization of PFHEs based on variable operating conditions instead of the conventional constant heat duty over the working period of the heat exchangers. To find the best suited evolutionary algorithm (EA) for the problem at hand, various widely used EAs are modified and tested on several practical problems. Moreover, since the heat exchanger design optimization is a highly constrained problem and the EAs are not equipped with constraint handling capabilities, conventional external strategies such as penalty function methods have been employed for this problem. The fine-tuning of the penalty parameters have been a drawback of using these methods, therefore a novel feasibility-based ranking strategy is proposed and utilized in the existing EAs. Using the proposed constrained EAs, the design of the PFHEs is presented based on entropy generation minimization (EGM) and economic considerations. Cross-flow PFHEs with offset strip fins on both sides are considered while method and the correlations available in the literature are employed for rating the heat exchangers. Illustrative case studies from literature are considered to show the efficiency and the accuracy of the proposed methods. The results of numerical tests show that the proposed approach finds the optimal design of PFHEs with superior accuracy and success rate in comparison with the available solutions in the literature.