Multi-Objective Optimization of Heat Exchanger Design by Entropy Generation Minimization

In the present work, a multi-objective optimization of heat exchanger thermal design in the framework of the entropy generation minimization is presented. The objectives are to minimize the dimensionless entropy generation rates related to the heat conduction under finite temperature difference and fluid friction under finite pressure drop. Constraints are specified by the admissible pressure drop and design standards. The genetic algorithm is employed to search the Pareto optimal set of the multi-objective optimization problem. It is found that the solutions in the Pareto optimal set are trade-off between the pumping power and heat exchanger effectiveness. In some sense, the optimal solution in the Pareto optimal set achieves the largest exchanger effectiveness by consuming the least pumping power under the design requirements and standards. In comparison with the single-objective optimization design, the multi-objective optimization design leads to the significant decrease in the pumping power for achieving the same heat exchanger effectiveness and presents more flexibility in the design process.

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