Investigation of heat-exchanger-sizing methods using genetic, pattern search, and simulated annealing algorithms and the effect of entropy generation
A numerical study on the heat exchanger design process has been conducted in order to propose a more effective method for the preliminary design of highly efficient and compact heat exchanger. The ε-NTU based performance prediction program and the heat exchanger database having performance correlations of various fin-type heat exchanger were developed. Numerical characteristics of the genetic, pattern search, and simulated annealing algorithms for the heat exchanger sizing were compared in terms of the accuracy and the computational speed. The effect of margins in design requirements were examined through the size ranking and the response surface analysis. The usefulness of the entropy generation minimization was appraised by comparing to the case when the objective function was the volume of the heat exchanger.
KeywordsHeat exchanger ε-NTU Optimization algorithm Entropy generation
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