Pore networks play a key role in understanding and quantifying flow and transport processes in complex porous media. Realistic pore-spaces may be characterized by singular regions, that is, isolated subnetworks that do not connect inlet and outlet, resulting from unconnected porosity or multiphase configurations. The robust identification of these features is critical for the characterization of network topology and for the solution of the set of linear equations of flow and transport. We propose a robust method based on singular value decomposition to solve for network flow and locate isolated subnetworks simultaneously. The performance of the method is demonstrated for pore networks of different complexity.

中文翻译：

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异质孔隙网络中单相流和团簇识别的奇异值分解


孔隙网络在理解和量化复杂多孔介质中的流动和传输过程方面发挥着关键作用。真实的孔隙空间可能以单一区域为特征，即由于未连接的孔隙度或多相配置而产生的不连接入口和出口的孤立子网。这些特征的稳健识别对于网络拓扑的表征以及流动和传输的线性方程集的求解至关重要。我们提出了一种基于奇异值分解的鲁棒方法来求解网络流并同时定位孤立的子网。该方法针对不同复杂度的孔隙网络进行了演示。