Pressure Drop and Interfacial Heat Transfer Coefficient Formulation for Packed Bed Systems with Cylindrical Capsules

Packed beds with cylindrical particles of polymeric material are a better option for developing low-cost, durable thermal energy storage for higher temperature ranges and corrosive environments. In this work, the formulations for pressure drop and interfacial convective heat transfer coefficient in the packed bed system (PBS) filled with cylindrical particles are developed for a wide range of geometrical and operating parameters. Two experimental setups are developed to determine the effects of superficial velocity, porosity of PBS, and geometrical dimensions of cylindrical particles on pressure drop and interfacial convective heat transfer coefficient. A discrete element method-based numerical model of PBS is developed to obtain the effect of fluid properties. The machine learning regression is deployed on the experimental and numerical data set to obtain a pressure drop formulation. Further, an analytical expression based on the Ergun equation is developed to approximate the machine-learning-based pressure drop formulation. The interfacial heat transfer coefficient is estimated by solving the steady-state heat conduction equation using the experimentally measured particle surface and air temperatures. The developed pressure drop and interfacial heat transfer coefficient formulations show maximum mean absolute deviations of less than 10.1% and 5.5%, respectively, with the experimental results.