Kinetic Theory of Granular Flows and Multi-scale CFD Modeling for Fluidized Beds

Kinetic Theory of Granular Flows and Multi-scale CFD Modeling for Fluidized Beds
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Total Pages : 157
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ISBN-10 : OCLC:954751589
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Book Synopsis Kinetic Theory of Granular Flows and Multi-scale CFD Modeling for Fluidized Beds by : Yujian Sun

Download or read book Kinetic Theory of Granular Flows and Multi-scale CFD Modeling for Fluidized Beds written by Yujian Sun and published by . This book was released on 2016 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fluidized beds are widely used in chemical industry for carrying out gas-solids reactions. Their advantages include superior heat transfer, low pressure drop compared to fixed beds, high throughput, and the ability to regenerate or reprocess the spent particles in a separate unit from the main reactor, when operated in a circulating fluidized bed mode. In spite of these desirable features, this type of gas-solids contactors also present challenges in understanding the detailed hydrodynamics, mixing and contacting pattern, as well as their effects on reactions. Design of commercial fluidized beds often requires scale-up from a smaller lab or pilot plant, but the behavior of the different scales must be linked by proper reactor models that take into account the possible changes in hydrodynamics and contacting patterns between the scales. This can be challenging because the prediction and extension of key parameters used in a model, such as axial dispersion number is usually not available, and phenomenological models for these parameters based on science are often missing. To meet these challenges, computational fluid dynamics, or CFD, can be utilized as a tool to extract the needed information by coarse-graining from the detailed hydrodynamics of the multiphase system, thus aiding in more rational design and scale-up of fluidized bed reactors. The CFD models in turn have their own parameters that need phenomenological models, which xii are easier to construct from fundamentals. Two types of simulation methods, i.e. Eulerian-Eulerian and Eulerian-Lagrangian, are investigated in this study. For the Eulerian method (also called two-fluid model, or TFM), in which the discrete solid particles are assumed as a continuous granular phase interpenetrated with the gas, the constitutive models for solids phase stress are needed. In this work, a new set of such models is developed from kinetic theory of granular flows with a new collision model. In this model, both the normal and tangential part of relative velocity between two colliding particles is damped due to inelastic collision, while the traditional model only takes into account the normal part. With this modification, the previously under-estimated dissipation rate of fluctuation energy is increased as expected. The models are implemented in OpenFOAM, an open-source CFD platform, to simulate a fluidized bed. The model improves the prediction of solids volume fraction without extra computational cost. In the Lagrangian or DEM (discrete element method) approach, the effort is motivated by Bhusarapus (2005) pioneering finding using CARPT (computer-aided radioactive particle tracking) that the traditional tracer method for measuring solids residence time distribution (RTD) cannot capture the actual residence time due to inability to distinguish the time that a particle temporarily spends out of the riser after first entry to or before last exit from the riser. By implementing the algorithm developed in this work to record separately the time that each particle actually spends in the riser, Lagrangian simulation is performed for a small circulating fluidized bed in OpenFOAM. The results clearly demonstrate the difference between RTD obtained from simulated traditional tracer method and that from the Lagrangian approach. Other information can be extracted as well such as the first passage time distribution, macromixing index, and interchange coefficient between a core region and an annular region, if using a core-annulus model. The potential capability of this CFD approach is boundless.


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