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首页> 外文期刊>Journal of Heat Transfer >Artificial Neural Networks in Radiation Heat Transfer Analysis
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Artificial Neural Networks in Radiation Heat Transfer Analysis

机译：辐射传热分析中的人工神经网络

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摘要

In the Monte Carlo ray-trace (MCRT) method, millions of rays are emitted and traced throughout an enclosure following the laws of geometrical optics. Each ray represents the path of a discrete quantum of energy emitted from surface element i and eventually absorbed by surface element j. The distribution of rays absorbed by the n surface elements making up the enclosure is interpreted in terms of a radiation distribution factor matrix whose elements represent the probability that energy emitted by element i will be absorbed by element j. Once obtained, the distribution factor matrix may be used to compute the net heat flux distribution on the walls of an enclosure corresponding to a specified surface temperature distribution. It is computationally very expensive to obtain high accuracy in the heat transfer calculation when high spatial resolution is required. This is especially true if a manifold of emissivities is to be considered in a parametric study in which each value of surface emissivity requires a new ray-trace to determine the corresponding distribution factor matrix. Artificial neural networks (ANNs) offer an alternative approach whose computational cost is greatly inferior to that of the traditional MCRT method. Significant computational efficiency is realized by eliminating the need to perform a new ray trace for each value of emissivity. The current contribution introduces and demonstrates through case studies estimation of radiation distribution factor matrices using ANNs and their subsequent use in radiation heat transfer calculations.
机译：在蒙特卡罗射线曲线（MCRT）方法中，在几何光学规则之后，在整个外壳中发射并追踪数百万光线。每种光线代表从表面元件I发射的离散量子的路径，并最终被表面元素j吸收。由辐射分布因子矩阵解释由所构成的N个表面元件吸收的光线分布，其元素表示由元素j吸收的元素j的能量的概率。一旦获得，分配因子矩阵可用于计算与指定的表面温度分布对应的外壳的壁上的净热通量分布。当需要高空间分辨率时，在计算出在传热计算中获得高精度是非常昂贵的。如果在参数研究中考虑发射率的歧义，则尤其如此，其中表面发射率的每个值需要新的射线迹线来确定相应的分布因子矩阵。人工神经网络（ANNS）提供一种替代方法，其计算成本大大不如传统的MCRT方法。通过消除对每个发射率的每个值执行新的光线迹线来实现显着的计算效率。目前贡献通过辐射分布因子矩阵使用ANN的估计来介绍和演示及其随后在辐射传热计算中使用。

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