Abstract This study examined the effects of an inclined elliptical cylinder on mixed convection in a square enclosure at three different Reynolds numbers, Re = 100, 500, and 1,000, and a fixed Grashof number of Gr = 105. The effects of the inclined angle of the elliptical cylinder (0° ≤ ϕ ≤ 180°) and aspect ratio on mixed convection were also analyzed by the distribution of the isotherms, streamlines, and the surface-averaged Nusselt number. The thermal and flow structures as well as the heat transfer performance were affected greatly by the inclined angle. In addition, the heat transfer performance for the variation in the inclined angle of the elliptical cylinder was predicted using an artificial neural network (ANN). The predicted values obtained from the ANN were matched well with the numerical data. The relative impact of the parameters on the heat transfer performance was estimated quantitatively. Overall, the heat transfer performance was affected in the order of the inclined angle, Reynolds number, and the aspect ratio.

中文翻译：

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使用人工神经网络预测椭圆圆柱盖驱动外壳中混合对流的传热性能

摘要 本研究检验了在三种不同雷诺数 Re = 100、500 和 1,000 以及固定 Grashof 数 Gr = 105 下，倾斜椭圆圆柱体对方形外壳中混合对流的影响。还通过等温线、流线和表面平均 Nusselt 数的分布分析了椭圆柱 (0° ≤ φ ≤ 180°) 和混合对流的纵横比。倾斜角度对热结构和流动结构以及传热性能有很大影响。此外，使用人工神经网络 (ANN) 预测椭圆圆柱倾斜角变化的传热性能。从人工神经网络获得的预测值与数值数据很好地匹配。定量估计参数对传热性能的相对影响。总体而言，传热性能按倾斜角、雷诺数和纵横比的顺序受到影响。