Multi-phase flow and transport in porous media is prevalent in a wide range of challenging fluid mechanics problems related to sustainability, energy, and the environment. Accurate prediction of the displacement and interaction of such flows is vital in addressing these problems. In particular it is critical to understand the small- or pore-scale flow and its spatial and temporal evolution, which can impact behaviors at system scales in a nontrivial manner. Intermittency is a phenomenon currently observed in numerical and experimental studies of single-phase flow (Anna et al., n.d.; Morales et al., n.d.), but the case of multi-phase flow has yet to receive much study due to challenges faced in both simulations and experiments. The underlying physics of spreading, mixing, and interfacial processes must be understood for accurate predictions of transport in multi-phase flow systems. Therefore, a comprehensive understanding of multi-phase flow at these very small scales is necessary in the development of accurate system-scale prediction models. We present results from a coordinated numerical and experimental study of intermittency effects over a range of viscous and inertial flow regimes in single- and multi-phase flows in 2D heterogeneous micromodels to quantify Lagrangian flow statistics to better inform pore-scale models. The applicability of different modeling frameworks such as the correlated-continuous time random walk is tested by studying statistics of particle trajectories obtained by particle tracking velocimetry (PTV) measurements and Lattice Boltzmann simulations from single- and multi-phase flows. The results make particular note of the influence of the pore Reynolds number (Re) and inertial effects on intermittency, and compare these effects in the two flow regimes.
Adaptive Mesh Refinement for a Finite Volume Method for Flow and Transport of Radionuclides in Heterogeneous Porous Media
