Thermodynamic Optimization of Plate-fin Heat Exchanger Using Teaching-learning- Based Optimization (tlbo) Algorithm
نویسندگان
چکیده
This study explores the use of teaching-learning-based optimization (TLBO) algorithm for thermodynamic optimization of a plate-fin heat exchanger. Minimizing the total number of entropy generation units for specific heat duty requirement under given space restrictions is considered as objective function. Based on the applications heat exchanger length, fin frequency, numbers of fin layers, lance length of fin, fin height and fin thickness are considered for optimization. Heat duty requirement constraint is included in the procedure. An application example is presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization using TLBO are validated by comparing with those obtained by using genetic algorithm (GA), particle swarm optimization (PSO) and artificial bee colony (ABC) algorithm.
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