Particle-fluid interactions under heterogeneous reactions

Particle-laden flows involve in many energy and industrial processes within a wide scale range. Solid fuel combustion and gasication, drying and catalytic cracking are some of the examples. It is vital to have a better understanding of the phenomena inside the reactors involving in particle-laden flows for process improvements and design. Computational fluid dynamics (CFD) can be a robust tool for these studies with its advantage over experimental methods. The large variation of length scales (101- 10-9 m) and time scales (days-microseconds) is a barrier to execute detailed simulations for large scale reactors. Current state-of-the-art is to use models to bridge the gap between small scales and large scales. Therefore, the accuracy of the models is key to better predictions in large scale simulations. Particle-laden flows have complexities due to many reasons. One of the main challenge is to describe how the particle-fluid interaction varies when the particles are reacting. Particle and the fluid interact through mass, momentum and heat exchange. Mass, momentum and heat exchange is presented by the Sherwood number (Sh), drag coefficient (CD) and Nusselt number (Nu) in fluid dynamics. Currently available models do not take into account for the effects of net gas flow generated by heterogeneous chemical reactions. Therefore, the aim of this research is to propose new models for CD and Nu based on the flow and temperature fields estimated by particle-resolved direct numerical simulations (PR-DNS). Models have been developed based on physical interpretation with only one fitting parameter, which is related to the relationship between Reynolds number and the boundary layer thickness. The developed models were compared with the simulation results solving intra-particle flow under char gasification. The drawbacks of models were identied and improvements were proposed. The models developed in this work can be used for the better prediction of flow dynamics in large scale simulations in contrast to the classical models which do not consider the effect of heterogeneous reactions. Better predictions will assist the design of industrial processes involving reactive particle-laden flows and make them highly effcient and low energy-intensive