Clarification of an improved cluster renewal model (ICRM) for heat transfer characteristics in a rolling circulating fluidized bed (RCFB)

This paper presents a novel method to predict the gas layer thickness δ′ in an improved cluster renewal model (ICRM) to calculate the heat transfer coefficient h′_c for a rolling circulating fluidized bed (RCFB). Eulerian-Eulerian two-fluid model (TFM) with kinetic theory of granular flow is used to perform a numerical simulation. After comparing the pressure gradient −△p/△z′ and the simulated heat transfer coefficient between multiphase and the wall h_gs with previously published experiment data, the correctness and reliability of the simulation are able to be verified. In conclusion, firstly, the variation of h′_c calculated from δ′ in the ICRM is almost the same with h_gs in the case that the RCFB undergoes the rolling motion. In order to quantitatively evaluate the proposed novel method, an error percentage α between h′_c calculated from δ′ and h_gs is 2.043% which is less than 5%. This certified that the novel method to predict δ′ in the ICRM has higher accuracy to calculate h′_c. Secondly, h′_c calculated from δ′ is mainly influenced by rolling amplitude Θ rather than by rolling period T. Specifically, with the increase of Θ, amplitudes of T_s are decreased, which is caused by the increased heat transfer and the decreased δ′ between cluster and wall. The decreased amplitudes of T_s are able to increase heat transfer efficiency, which eventually increases h′_c. Thirdly, in the case that normalized rolling period t/T is changed from 0 to 0.5, higher h′_c calculated from δ′ in Region Ⅰ results from the large local cross-sectional particle volume fraction c_local in Region Ⅰ with a smaller δ′, while lower h′_c calculated from δ′ in Region III results from the smaller c_local in Region III with a larger δ′. Therefore, it is concluded that h′_c calculated from δ′ is able to well predict the bed-to-wall heat transfer coefficient of the RCFB even if the rolling motion is considered.