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首页> 外文期刊>Journal of Physics, D. Applied Physics: A Europhysics Journal >Randomly mixed model for predicting the effective thermal conductivity of moist porous media
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Randomly mixed model for predicting the effective thermal conductivity of moist porous media

机译:随机混合模型,用于预测潮湿多孔介质的有效导热系数

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摘要

A randomly mixed model is developed for the prediction of the effective thermal conductivity of a multi-phase system. The proposed model is based on the assumption that the smallest part of the phases is a cube, and all the cubes are randomly dispersed in the space. The effective thermal conductivity therefore can be found numerically from thermal conductivities and volume fractions of the components, using the principle of heat conduction in anisotropic media. The prediction does not depend upon empirical parameters and the algorithm is easy to perform in a personal computer. The validation of the proposed model is tested by several types of moist porous media with various porosities and degrees of saturation. Compared with the experimental data of the soils and building materials, the proposed model can give a fine prediction of the moist porous media for porosity less than 0.6. Finally, the deviations between the predicted and experimental results for high porosity are also analysed.
机译:建立了一个随机混合模型来预测多相系统的有效导热系数。提出的模型基于以下假设:相的最小部分是一个立方体,并且所有立方体都随机分散在空间中。因此,可以利用各向异性介质中的热传导原理,从组分的热导率和体积分数从数值上找到有效的热导率。该预测不依赖于经验参数,并且该算法易于在个人计算机中执行。通过几种类型的具有不同孔隙率和饱和度的潮湿多孔介质测试了所提出模型的有效性。与土壤和建筑材料的实验数据相比,该模型可以较好地预测孔隙度小于0.6的潮湿多孔介质。最后,还分析了高孔隙率的预测结果与实验结果之间的偏差。

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