Percolation and conductivity in evolving disordered media
Percolation and conductivity in evolving disordered media
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不断演化的无序介质中的渗流和电导率
DOI：
10.1103/physreve.108.024132
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发表时间：
2023
影响因子：
2.4
通讯作者：
Sahimi, Muhammad
中科院分区：
文献类型：
--
作者：
Berg, Carl Fredrik;Sahimi, Muhammad
渗透理论和相关的电导网络为大量非均质材料和介质的流动和输运特性提供了深刻的见解。然而，在几乎所有的情况下，网络键的电导在整个过程中保持不变。然而，在许多重要的问题中，化学键的电导会随着时间的推移而变化，而不是保持不变。例如，多孔材料中的堵塞、溶解和沉淀、催化过程，以及通过施加外部压力或应力使多孔介质变形，从而减小其孔隙的大小。我们引入了两个渗流模型来研究这种网络的电导率的演化。这两个模型与自然和工业过程有关，涉及多孔介质和材料中的堵塞、沉淀和溶解过程。模型的有效电导率在渗流阈值附近遵循已知的幂律，尽管在远离渗流阈值和接近渗流阈值时的行为完全不同。接近渗透阈值的网络行为用临界指数来描述，得到传统渗透指数的边界。我们证明了其中一个模型属于传统的普适性渗透电导率类，而第二个模型产生非普适性标度指数。
Percolation theory and the associated conductance networks have provided deep insights into the flow and transport properties of a vast number of heterogeneous materials and media. In practically all cases, however, the conductance of the networks' bonds remains constant throughout the entire process. There are, however, many important problems in which the conductance of the bonds evolves over time and does not remain constant. Examples include clogging, dissolution and precipitation, and catalytic processes in porous materials, as well as the deformation of a porous medium by applying an external pressure or stress to it that reduces the size of its pores. We introduce two percolation models to study the evolution of the conductivity of such networks. The two models are related to natural and industrial processes involving clogging, precipitation, and dissolution processes in porous media and materials. The effective conductivity of the models is shown to follow known power laws near the percolation threshold, despite radically different behavior both away from and even close to the percolation threshold. The behavior of the networks close to the percolation threshold is described by critical exponents, yielding bounds for traditional percolation exponents. We show that one of the two models belongs to the traditional universality class of percolation conductivity, while the second model yields nonuniversal scaling exponents.