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首页> 外文期刊>Journal of Quantitative Spectroscopy & Radiative Transfer >Prediction of radiative heat transfer in 3D complex geometries using the unstructured control volume finite element method
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Prediction of radiative heat transfer in 3D complex geometries using the unstructured control volume finite element method

机译:使用非结构化控制体积有限元方法预测3D复杂几何中的辐射传热

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摘要

In this paper, a 3D algorithm for the treatment of radiative heat transfer in emitting, absorbing, and scattering media is developed. The numerical approach is based on the utilization of the unstructured control volume finite element method (CVFEM) which, to the knowledge of the authors, is applied for the first time to simulate radiative heat transfer in participated media confined in 3D complex geometries. This simulation makes simultaneously the use of the merits of both the finite element method and the control volume method. Unstructured 3D triangular element grids are employed in the spatial discretization and azimuthal discretization strategy is employed in the angular discretization. The general discretization equation is presented and solved by the conditioned conjugate gradient squared method (CCGS). In order to test the efficiency of the developed method, several 3D complex geometries including a hexahedral enclosure, a 3D equilateral triangular enclosure, a 3D L-shaped enclosure and 3D elliptical enclosure are examined. The results are compared with the exact solutions or published references and the accuracy obtained in each case is shown to be highly satisfactory. Moreover, this approach required a less CPU time and iterations compared with those of even parity formulation of the discrete ordinates method.
机译:在本文中,开发了一种用于处理发射,吸收和散射介质中的辐射热传递的3D算法。数值方法是基于非结构化控制体积有限元方法(CVFEM)的利用,据作者所知,CVFEM是首次应用于模拟受限于3D复杂几何形状的参与介质中的辐射传热。该模拟同时利用了有限元法和控制量法的优点。在空间离散化中使用非结构化3D三角形元素网格,在角度离散化中使用方位角离散化策略。提出了一般离散方程,并通过条件共轭梯度平方方法(CCGS)求解。为了测试所开发方法的效率,研究了几种3D复杂几何形状,包括六面体外壳,3D等边三角形外壳,3D L形外壳和3D椭圆形外壳。将结果与精确的解决方案或已发表的参考文献进行比较,并且在每种情况下获得的准确性都非常令人满意。此外,与离散纵坐标方法的均匀校验公式相比,此方法所需的CPU时间和迭代次数更少。

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