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A new computational method for studying heat transfer in fluid bed reactors
Authors:ZY Zhou  AB Yu  P Zulli
Affiliation:1. Lab for Simulation and Modelling of Particulate Systems, School of Materials Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia;2. BlueScope Steel Research, P.O. Box 202, Port Kembla, NSW 2505, Australia;1. Catalyst & Process R&D Center, SK Innovation, DaeJeon 305-712, Republic of Korea;2. Department of Chemical and Biomolecular Engineering and Energy & Environment Research Center, Korea Advanced Institute of Science and Technology (KAIST), DaeJeon 305-701, Republic of Korea;1. School of Materials Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia;2. Laboratory for Simulation and Modelling of Particulate Systems, Department of Chemical Engineering, Monash University, Clayton, VIC 3800, Australia;3. Department of Mechanical Engineering, Sultan Ageng Tirtayasa University, Jl. Jend. Sudirman KM 3, Cilegon, Banten, Indonesia
Abstract: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.
Keywords:
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