Mesoscopic predictions of the effective thermal conductivity for microscale random porous media.
Mesoscopic predictions of the effective thermal conductivity for microscale random porous media.
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DOI：
10.1103/physreve.75.036702
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发表时间：
2007-03
期刊：
影响因子：
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通讯作者：
Moran Wang;Jinku Wang;N. Pan;Shiyi Chen
中科院分区：
文献类型：
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作者：
Moran Wang;Jinku Wang;N. Pan;Shiyi Chen
本研究开发了一种用于预测微尺度随机多孔介质有效导热系数的介观数值工具。为了求解具有复杂多相多孔结构的能量输运方程，引入了格子Boltzmann算法来处理不同相间的共轭换热。在正确选择边界条件的情况下，通过与较简单情况下的理论解和现有实验数据的比较，初步验证了该算法的有效性。此外，为了反映大多数多孔介质的随机相分布特征，基于随机簇生长理论，提出了一种随机内部形态和结构生成-生长方法，称为四重态结构生成集(QSGS)，以生成更真实的多孔介质微结构。因此，利用目前的格子Boltzmann算法和结构生成工具QSGS，我们可以预测具有多相结构和随机复杂几何形状的多孔介质的有效导热系数，而不需要逐个确定任何经验参数。该方法已被应用于几个两相和三相系统，其结果与已发表的实验数据吻合较好，从而证明了该方法是严谨、通用和稳健的。除了传统的多孔介质外，本方法也适用于处理其他多相混合物、合金和多组分复合材料。
A mesoscopic numerical tool has been developed in this study for predictions of the effective thermal conductivities for microscale random porous media. To solve the energy transport equation with complex multiphase porous geometries, a lattice Boltzmann algorithm has been introduced to tackle the conjugate heat transfer among different phases. With boundary conditions correctly chosen, the algorithm has been initially validated by comparison with theoretical solutions for simpler cases and with the existing experimental data. Furthermore, to reflect the stochastic phase distribution characteristics of most porous media, a random internal morphology and structure generation-growth method, termed the quartet structure generation set (QSGS), has been proposed based on the stochastic cluster growth theory for generating more realistic microstructures of porous media. Thus by using the present lattice Boltzmann algorithm along with the structure generating tool QSGS, we can predict the effective thermal conductivities of porous media with multiphase structure and stochastic complex geometries, without resorting to any empirical parameters determined case by case. The methodology has been applied in this contribution to several two- and three-phase systems, and the results agree well with published experimental data, thus demonstrating that the present method is rigorous, general, and robust. Besides conventional porous media, the present approach is applicable in dealing with other multiphase mixtures, alloys, and multicomponent composites as well.