Conjugate Heat Transfer in Porous Cavity: ANN approach

被引:1
|
作者
Kazi, Mohammed Jafer [1 ]
Khan, T. M. Yunus [2 ]
机构
[1] Doosan Heavy Ind & Construct, POB 2031, Mishref 40171, Kuwait
[2] BVB Coll Engn & Technol, Depatment Mech Engn, Hubli, India
来源
INTERNATIONAL CONFERENCE ON MATERIALS, ALLOYS AND EXPERIMENTAL MECHANICS (ICMAEM-2017) | 2017年 / 225卷
关键词
Porous medium; Artificial Neural Network (ANN); Nusselt number; NATURAL-CONVECTION; VISCOUS DISSIPATION; MASS-TRANSFER; RADIATION; ANNULUS;
D O I
10.1088/1757-899X/225/1/012015
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Artificial neural network is a technique to predict the outcome of a function depending on various input parameters that could be either or geometric variables. This technique is widely used in many fields to predict an outcome. The current article discusses the usage of artificial neural network to predict conjugate heat transfer behaviour inside the porous cavity. The artificial neural network is run with neurons placed in multiple layers. The heat transfer inside the porous cavity is predicted in terms of Nusselt number which shows the convective heat transfer in relation to its conduction counterpart. The heat transfer prediction is compared with the results obtained by finite element method.
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收藏
页数:5
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