A new computational method for studying heat transfer in fluid bed reactors

Effective thermal conductivity (ETC) is an important parameter describing the thermal behaviour of packed beds with a stagnant or dynamic fluid, and has been extensively examined in the past decades. Recently, an approach of coupled discrete particle simulation (DPS) and computational fluid dynamics (CFD) has been extended to predict the ETC, allowing the elucidation of the underlying heat transfer mechanisms at a particle scale. However, because of the sensitivity of heat transfer to particle–particle contact, a large Young's modulus and small time step have to be employed in the DPS to generate accurate results, resulting in a high computational cost. This paper proposed a method to overcome this problem. It is done by introducing a correction coefficient in the calculation of the particle–particle contact radius between colliding particles. The treatment is first implemented in our recent DPS-CFD modeling of the heat transfer in gas fluidization, and is validated by comparing the predicted ETC with literature data. The effects of model parameters, particle size, and bed average temperature on ETC are also analyzed.

A new computational method is proposed to predict the effective thermal conductivity (ETC) of a packed bed, in which a correction coefficient is introduced in the calculation of the particle–particle contact radius between colliding particles to reduce computational time. The predicted ETC agrees well with those measured. The proposed approach can examine the heat transfer in fluid bed reactors at a particle scale.Figure optionsDownload as PowerPoint slide