Today, such models involve using computational fluid dynamics. Inherent knowledge of the bubble properties is not required. However, the spatial resolution of the computational domain is a trade-off between the accuracy of the bubble properties and the simulation time. So, which is better or more appropriately, which model should be used and when. This talk will focus on the merits, compromises, and limitations of these models.
Reduced Order and Higher Order Models for Bubbling Fluidized Bed Reactors
Fluidized bed reactors offer some of the most complicated hydrodynamics that a chemical engineer could experience. For fast reactions, being able to capture the bubble hydrodynamics is paramount in developing a model useful for scale-up. D. Kunii and Octave Levenspiel first addressed this with their bubbling fluidized bed model where the gas flow through the bed is modeled through uniformly sized bubbles, surrounded by clouds and followed by wakes, rising through an emulsion of downward moving solids. Interchange of gas occurs continuously among bubble, cloud-wake, and emulsion regions. The model contains one key parameter, the bubble size, and all internal flow and interchanges in the bed are derived from it. It was a simple useful model providing the bubble size was captured.
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