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Multi-Objective Optimization of a Plain Fin-and-Tube Heat Exchanger Using Genetic Algorithm

机译:基于遗传算法的平面管翅式换热器多目标优化

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In the present paper, a plate fin-and-tube heat exchanger (PFTHE) is considered for optimization with air and water as working fluid, four geometric variables are taken as parameters for optimization, a Genetic Algorithm (GA) was used to search for the optimal structure sizes of the PFTHE, the maximum total heat transfer rate and the minimum total pressure drop are taken as objective functions in GA, respectively. Performance of the optimized result was evaluated and correspondingly the total heat transfer rate, the total pressure drop, the heat transfer coefficient and the local Nusselt numberj-factor and friction factor ζ, are calculated respectively. Results show that the total heat transfer rate of the optimized heat exchanger increased by about 2.1-9.2% comparing with the original one, the heat transfer coefficient increased by about 8.2-14.7% and the total pressure drop decreased by about 4.4-8% in the range of Re = 1200-14000.
机译:本文考虑以空气和水为工作流体对板翅管式换热器(PFTHE)进行优化,以四个几何变量作为优化参数,并采用遗传算法(GA)进行搜索。在GA中,PFTHE的最佳结构尺寸,最大总传热率和最小总压降分别作为目标函数。评估了优化结果的性能,并分别计算了总传热速率,总压降,传热系数和局部Nusselt数j因子和摩擦因子ζ。结果表明,优化后的换热器总传热率比原来提高了约2.1-9.2%,换热系数提高了约8.2-14.7%,总压降降低了约4.4-8%。 Re的范围= 1200-14000。

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