Abstract
Porous media compressed air energy storage (PM-CAES) is an emerging technology that stores compressed air in an underground aquifer during the off-peak periods, to mitigate the mismatch between energy supplies and demands. Thus, PM-CAES involves repeated two-phase fluid flow in porous media, and ensuring the success of PM-CAES requires a better understanding of repetitive two-phase fluid flow through porous media. For this purpose, we previously developed microfluidic channels that retain a two-dimensional (2D) pore network. Because it was found that the geometry of the pore structure significantly affects the patterns and occupational efficiencies of a non-wetting fluid during the drainage-imbibition cycles, a more realistic microfluidic model is needed to reflect the three-dimensional (3D) nature of pore structures in the underground geologic formation.
In this study, we developed an easy-to-adopt method to fabricate a microfluidic device with a 3D random pore network using a sacrificial sugar template. Instead of using a master mold made in photolithography, a sacrificial mold was made using sugar grains so that the mold could be washed away after PDMS curing. First, we made sugar templates with different levels of compaction load, and found that the thickness of the templates decreased as the compaction load increased, which suggests more packing of sugar grains and thus lower porosity in the template. Second, we fabricated PDMS porous media using the sugar template as a mold, and imaged their pore structure using micro computed tomography (micro-CT). Pores within PDSM samples appeared more tightly packed as the compacting force increased. Last, we fabricated a prototype PDMS channel device with a 3D pore network using a sugar template, and visualized flow through the pore network using colored water. The flow visualization result shows that the water was guided by the random pores and that the resultant flow pattern was three dimensional.
Interface Capturing for Immiscible Two-phase Fluid Flows by THINC Method
