Computational Modeling in Fluidization Engineering

Dear Colleagues,

In large-scale processes where fluidized bed reactors are employed, such as in the petroleum, pharmaceutical, and food industries, the optimal operating conditions are determined through trials in existing installed fluidized units or experiments in similarly configured pilot plants. Despite the high costs, detailed experiments provide highly reliable data concerning the process that can help in unit design, but the optimal operating conditions obtained at the pilot scale are not always extrapolatable to larger devices. In this regard, the computational modeling of fluidized beds allows for the understanding and optimization of inherently complex systems involving the exchange of momentum between liquids or gases and solids, with the simultaneous or non-simultaneous development of mass and energy transfer and chemical reactions.

The models commonly employed with a necessarily computational resolution can be formulated on a local or global scale, based on thermodynamics, kinetics, phenomenology, neural networks, or computational fluid dynamics. Although each approach presents different challenges, the results ultimately allow for a more detailed understanding of each process at a relatively low cost and within tight timeframes, even enabling the expansion in the range of experimental operational conditions studied and the identification of process safety-related operational limits.

Prof. Dr. Germán Mazza
Guest Editor

Dr. César Venier
Dr. Andrés Reyes Urrutia
Guest Editor Assistants

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• fluidized bed contactors
• modeling of processes
• thermodynamic models
• kinetic models
• neural networks
• computational fluid dynamics (CFD)
• optimal operating conditions
• process safety