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Analysis and optimization of fan-shaped pin-fin in a rectangular cooling channel

机译:矩形冷却通道中扇形翅片的分析和优化

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The heat transfer performance of a new fan-shaped pin-fin in a rectangular cooling channel is evaluated using three-dimensional Reynolds-averaged Navier-Stokes equations in comparison with a circular pin-fin. A multi-objective optimization of the fan-shaped pin-fin was performed using a hybrid evolutionary algorithm with surrogate modeling to maximize the heat transfer and to minimize the friction loss simultaneously. The fluid flow and heat transfer were analyzed using the shear stress transport turbulence model in the Reynolds number range of 5000-100,000. The results of our analysis indicate that the averaged Nusselt number with the fan-shaped pin-fin was improved considerably in comparison with that of the circular pin-fin over the whole range of Reynolds numbers. For the optimization of the fan-shaped pin-fin, the ratio of the radius of front part of the pin-fin to that of the rear part, and the lateral reduction angle of the pin-fin, were selected as the design variables. Fifteen design points were generated using Latin hypercube sampling, and the values of the objective function were evaluated at these points. The surrogate models for the objective functions were constructed using the radial basis neural network method. The Pareto-optimal solutions of the fan-shaped pin-fin show that the designs were improved with respect to heat transfer and pressure drop in comparison with the circular and reference pin-fins.
机译:使用三维雷诺平均Navier-Stokes方程与圆形针状翅片进行比较,评估了矩形冷却通道中新型扇形针状翅片的传热性能。使用具有替代模型的混合进化算法对扇形销钉鳍进行多目标优化,以最大程度地提高热传递并同时最小化摩擦损失。使用切应力传输湍流模型在5000-100,000的雷诺数范围内分析了流体的流动和传热。我们的分析结果表明,在整个雷诺数范围内,扇形针状鳍片的平均努塞尔特数与圆形针状鳍片的平均努素数相比有显着提高。为了优化扇形针状翅片,选择了针状翅片的前部半径与后部半径的比率以及针状翅片的横向减小角度作为设计变量。使用拉丁超立方体采样生成了15个设计点,并在这些点上评估了目标函数的值。使用径向基神经网络方法构建目标函数的替代模型。扇形针状鳍的帕累托最优解表明,与圆形和参考形针状鳍相比,设计在传热和压降方面得到了改进。

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