Ganglia, or bubbles, trapped by capillary forces inside porous materials occur in a wide range of subsurface and manufacturing applications. In geologic CO₂ storage, ganglia are desired as they render the injected CO₂ hydrodynamically immobile. But they may evolve by dissolution or mass exchange across the brine, called ripening. In fuel cells and electrolyzers, water/oxygen ganglia must be removed to ensure optimal performance of the device. In both applications, the porous microstructure plays a key role in how the geometry/topology of ganglia evolve as they grow/shrink in size. This dependence is poorly understood but important for controlling ganglion dynamics. Pore-scale models are useful tools for probing the physics, but existing ones are either computationally expensive (e.g., CFD) or incapable of accurately simulating ganglia spanning multiple pores (e.g., pore networks). Our main contribution is a new pore-network model (PNM) that removes this barrier. The PNM can simulate the evolution of multi-pore occupying ganglia due to diffusive mass transfer by ripening or an external concentration field. We validate the PNM against published microfluidic experiments, 2D direct numerical simulations, and an analytical solution previously derived by the authors for a 2D homogeneous domain. We then use the PNM to study quasi-static growth-shrinkage cycles of trapped ganglia inside heterogeneous porous media. The findings constitute our second contribution, generalizing previous theoretical results by the authors from 2D homogeneous to 3D-planar heterogeneous microstructures. They include: (1) the interfacial area of a ganglion depends approximately linearly on its volume; (2) if the throat-to-pore aspect ratio is large, growth is percolation-like; but (3) if it is small, a hitherto unreported intermittent growth regime precedes percolation, in which ganglia repeatedly fragment and reconnect. These outcomes have implications for selecting optimal storage sites for CO₂ and designing fuel cells and electrolyzers with finetuned porous microstructures.

被多孔材料内部的毛细力捕获的神经节或气泡出现在广泛的地下和制造应用中。在地质 CO ₂储存中，需要使用神经节，因为它们可以提供注入的 CO ₂流体动力学不动。但它们可能通过盐水的溶解或质量交换而进化，称为成熟。在燃料电池和电解槽中，必须去除水/氧神经节以确保设备的最佳性能。在这两种应用中，多孔微结构在神经节的几何形状/拓扑结构如何随着它们的尺寸增长/缩小而演变中发挥着关键作用。这种依赖性知之甚少，但对控制神经节动力学很重要。孔隙尺度模型是探索物理学的有用工具，但现有模型要么计算量大（例如，CFD），要么无法准确模拟跨越多个孔隙（例如，孔隙网络）的神经节。我们的主要贡献是消除了这一障碍的新孔隙网络模型（PNM）。PNM 可以模拟由于成熟或外部浓度场的扩散传质引起的多孔占据神经节的演变。我们针对已发表的微流体实验、2D 直接数值模拟以及作者先前为 2D 均匀域导出的解析解来验证 PNM。然后，我们使用 PNM 研究异质多孔介质内被困神经节的准静态生长-收缩循环。这些发现构成了我们的第二个贡献，将作者先前的理论结果从 2D 均质微结构推广到 3D 平面异质微结构。它们包括：（1）神经节的界面面积近似线性地取决于它的体积；(2) 喉孔纵横比大时，生长呈渗流状；但是（3）如果它很小，迄今为止未报道的间歇性增长机制先于渗透，其中神经节反复分裂和重新连接。这些结果对选择二氧化碳的最佳储存地点有影响₂并设计具有微调多孔微结构的燃料电池和电解槽。