Flow analysis through a randomly packed pebble-bed geometry using computational fluid dynamics Academic Article uri icon

abstract

  • This study presents a comprehensive analysis of the flow behavior in packed pebble-bed reactors using computational fluid dynamics (CFD) simulations. The pebble-bed geometry corresponds to an experimental facility located at the Texas A&M Thermal-Hydraulics Research Laboratory. The unsteady Reynolds-averaged NavierStokes (URANS) k shear stress transport (SST) and the large eddy simulation (LES) approaches were selected to model the turbulence at different Reynolds numbers. The numerical models were first validated by comparing the pressure drop results obtained from the simulations against established correlations, finding the simulation predictions in accurate agreement. Secondly, the velocity first-order statistics from the URANS k SST and LES calculations were also contrasted with the available experimental particle image velocimetry data to validate the numerical models. Results were found in reasonable agreement as the mean absolute error achieved values smaller than 10% of the inlet velocity for most of the analyzed velocity profiles. A comprehensive turbulence characterization was performed, including second-order statistics, Reynolds stress anisotropy, and turbulent kinetic energy production. The proper orthogonal decomposition of the fluctuating velocity was examined in the current flow domain. The turbulence characterization revealed the complex nature of turbulence in packed pebble-bed geometries, which is further complicated by the presence of an enclosing wall. Overall, the findings of this study provide a solid foundation for the development of more accurate CFD-based methodologies for predicting the behavior of flow through packed pebble-bed reactors.

published proceedings

  • Physics of Fluids

author list (cited authors)

  • Lanade, D., Davalos, O. B., Menezes, C., & Hassan, Y.

citation count

  • 1

complete list of authors

  • Lanade, David||Davalos, Octavio Bovati||Menezes, Craig||Hassan, Yassin

publication date

  • February 2024