Flow Resistance of Randomly Packed Beds of Crushed Rock and Ellipsoidal Particles using CFD

Abstract

Rock bed thermal energy storage is a cost-effective solution to store waste heat from a solarized Brayton cycle for use in a Rankine cycle after sunset. However, rock bed thermal energy storage systems for utility scale concentrated solar power are huge and require multiple air inlets and outlets. As a result, the flow inside the bed is fully three dimensional and deviates considerably from plug flow conditions usually encountered in chemical reactors. Designing a rock bed thermal energy storage system for the minimum capital cost and pumping power depend on reliable predictions of the fluid flow paths and temperature profiles in the bed. Particle size and shape have a significant influence on how the particles will pack down, which in turn influences the flow pattern in the bed, and hence the pressure drop and heat transfer characteristics of the bed. In this work, we discuss the characterization of crushed rock particles and concluded that there are benefits in approximating particles by mono-dispersed ellipsoids. We used discrete element modelling to generate packed beds of the ellipsoidal particles, and computational fluid dynamics to model the flow in the interstitial voids. This way, we successfully captured the directional effect of the flow resistance for ellipsoidal particles in terms of sphericity, , porosity , particle diameter Dve, and particle Reynolds number ReOur current model under-predicted the pressure drop across a packed bed of crushed rock particles.

A DEM-CFD Approach for Predicting Pressure Drop Through Packed Bed of Crushed Rocks

“…The computed standard deviation from the mean for diagonal and non-diagonal elements was less than 8%. Equation 7 is similar to that proposed by Hoffmann et al [19], in which they stated that the power law of Re p equal to (-0.…”