A discrete element approach to model packed bed thermal storage. (1st November 2022)

• Record Type: Journal Article
• Authors: Gaviño, David; Cortés, Eduardo; García, Jesús; Calderón-Vásquez, Ignacio; Cardemil, José; Estay, Danilo; Barraza, Rodrigo
• Is Part Of: Applied energy. Volume 325(2022)
• Publication Date: 2022-11-01
• Subjects: Pack bed thermal energy storage -- Thermal analysis -- Simulation and radiation heat exchange -- Numerical modeling -- Sensible heat storage -- Thermal stratification; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2022.119821
• Languages: English
• ISSNs: 0306-2619

Abstract

Abstract: A discrete 1-D Eulerian and 3-D Lagrangian model was developed to analyze heat transfer in packed beds composed of spherical particles to study a in more detail the solid phase phenomenon. The proposed thermal model simulates the particles using the discrete element method, generating a particle distribution inside the packed bed. It considers direct and indirect conduction, convection, and radiation and evaluates the local heat transfer phenomena. One of its main advantages is its flexibility to deliver results at the particle level, which provides detailed information than continuous models. A comparison with experimental data from the literature indicates good agreement, with mean absolute errors lower than 8 K. Finally, through a sensitivity analysis, it was demonstrated that the selection of an appropriate Nusselt number is essential because it is related to the convective heat transfer, which corresponds to 85.8% of the total heat transfer during the charging process. For the standby process, particle fluid conduction is the predominant heat transfer mechanism, accounting for 27.5% of the total heat transfer. Highlights: The implementation of a two-phase transient thermal discrete model is presented. The model captures the influence of the non-homogeneity porosity in the packed bed. The model is validated with experimental data, obtaining MAE lower than 8 K . A sensitivity analysis is made with the main parameters in the thermal simulation. The correct choice of convection correlation is key to obtain good results.