(584f) New Correlations for Interphase Drag in Two-Fluid Models to Predict the Pressure Drop across a Packed Bed Reactor

Porous media are essential in a plethora of transport phenomena applications from water treatment systems to heat pipes. For example, packed bed reactors (PBRs) consist of tightly packed spherical particles within a cylindrical or cuboidal container. Fluid flows in the interconnected interstitial space between the particles. Quantifying the pressure drop due to flow through a PBR is essential for engineering PBRs for particular applications. Recently, experiments were conducted on the International Space Station (ISS) to investigate the pressure drop and gas-liquid flow regimes within a PBR at microgravity conditions. In this work, we develop a two-fluid model (TFM) calibrated against the data collected on the ISS. Two closure relations are needed for the TFM: the liquid-solid f_{ls} and gas-liquid f_{gl} interphase forces. We use an Ergun-type closure for f_{ls} by assuming complete liquid wetting of the solid particles in the PBR. Under a 1D flow assumption, the TFM equations are rewritten with f_{gl} as the only unknown. We develop a novel correlation for f_{gl} based data-driven optimization against the pressure gradient data from the ISS experiments. Further, f_{gl} is determined for each gas and liquid flow rate in the experiments so that it can be fit as a function of the liquid and gas Reynolds numbers, Re_{l} and Re_{g} respectively, and the Suratman number Su_{l}, which is a ratio of surface tension to the momentum transport. To validate the proposed f_{gl}(Re_{l},Re_{g},Su_{l}) closure, we perform 2D transient, multiphase computational fluid dynamics simulations at low Re_{l} and Re_{g} (laminar flow) in ANSYS Fluent employing an Euler-Euler formulation. The closure relations for f_{ls} and f_{gl} are encoded as user-defined functions that introduce source terms in the momentum equations. From these 2D simulations, we find good agreement between the steady-state pressure drop across the PBR predicted using the proposed f_{gl} closure and the data collected during the ISS experiments. This closure relationship can leveraged to predict pressure drops in other gas-liquid flows in porous media.

This research was supported by the National Aeronautics and Space Administration under grant number 80NSSC22K0290.