Development of kinetic theory-based models for modelling of adhesive granular flows
Fluidized bed reactor systems find numerous applications in a variety of industries including Pharmaceutical, Chemical, Food Processing and Oil & Gas applications.
Research Opportunities
Summary
Fluidized beds are basically multiphase systems comprising dilute and dense pockets of particles which are aerated by passing a carrier gas through it. In the context of Fluidised Catalytic Cracking (FCC) reactors, the catalyst particles are charged due to attrition resulting from repeated collisions and theri sizes span several order of magnitude. The charged particles are prone to agglomeration due to the Van der Waals effect. Clustering of particles could also be induced by the turbulent eddies in the gas medium in conjunction with the electrical properties of the particles. Clustering of particles has a significant effect on the contact time between the gas and particle phases and thus the efficient of the reactor. A tractable approach to model such systems is to treat the particle phase as a pseudo-fluid with its own thermodynamic properties (viscosities and pressure), typically referred to as the Kinetic-Theory Granular Flow (KTGF) approach. The different agglomeration process mentioned above result in agglomerates interacting with each other. The aim of the present research is to extend the KTGF framework to account for collision between these particle-like entities.
The proposed project will improve understanding of the scale of agglomerates formed during particle clustering processes in these reactors. Further, the research will investigate the effect of particle clustering on the macro-scale fluctuations i.e. turbulent kinetic energy of the particle phase.
The proposed research methodology is a mix of fully-resolved simulations using the immersed boundary method (IBM) and macro-scale averaged simulations using the KTGF approach. A data-driven approach will be undertaken to close the terms in the KTGF model accounting for adhesion between particles using the fully resolved simulations. The attractive feature of the proposed methodology is that it can be extended to incorporate further parameters such as surface roughness of the particles. Developing reliable macro-scale models will enable full-scale analysis of fluidized bed systems including ancillary components like cyclones and stand-pipes. This will enable rapid translation of learnings from pilot-scale systems to efficiency improvements in full-scale reactors.
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