Multiobjective geometry optimization of microchannel heat exchanger using real-coded genetic algorithm

被引：36

作者：

Garcia, John Carlo S. ^{[1
,2
]}

Tanaka, Hiroki ^{[1
]}

Giannetti, Niccolo ^{[3
,4
]}

Sei, Yuichi ^{[5
]}

Saito, Kiyoshi ^{[1
,4
]}

Houfuku, Mamoru ^{[6
]}

Takafuji, Ryoichi ^{[6
]}

机构：

[1] Waseda Univ, Dept Appl Mech & Aerosp Engn, Tokyo 1698555, Japan

[2] Univ Philippines, Dept Mech Engn, Quezon City 1101, Philippines

[3] Waseda Univ, Waseda Inst Adv Study, Tokyo 1698050, Japan

[4] Waseda Univ, Interdisciplinary Inst Thermal Convers Engn & Mat, Tokyo 1698555, Japan

[5] Univ Electrocommun, Dept Informat, Tokyo 1828585, Japan

[6] Hitachi Johnson Controls Air Conditioning Inc, 500 Tomida,Ohira Machi, Tochigi City, Tochigi 3294404, Japan

来源：

APPLIED THERMAL ENGINEERING | 2022年 / 202卷

关键词：

Microchannel heat exchanger; Optimization; Real-coded genetic algorithm; TRANSFER PERFORMANCE; FLOW DISTRIBUTION; PARAMETERS; DESIGN; SINK;

D O I：

10.1016/j.applthermaleng.2021.117821

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

In this paper, a multiobjective optimization of the structure of a flat-tubed microchannel heat exchanger is performed to reduce its volume and fan power at a specified capacity. Design variables include tube height, tube width, tube length, fin height, and fin pitch. A weight-based, real-coded genetic algorithm is implemented to optimize the design variables within their specified range of dimensions. To further improve the numerical simulations of the microchannel heat exchanger performance, correlations for the air-side Nusselt number, friction factor, and fin efficiency are developed and validated. In the optimization, the Pareto optimal fronts are obtained by varying weights of the two conflicting objectives. A reference microchannel heat exchanger operating at different capacities is optimized. Results show that the volume and fan power of the reference microchannel heat exchanger can be reduced by up to 45% and 51% respectively, depending on the weighting factor selected. The optimization approach of this study provides the optimal solutions at the given domain of geometric parameter dimensions.

引用

页数：13

共 48 条

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