Coupled particle–ﬂuid ﬂow can be observed in almost all types of particulate processes which are widely used in industry. Essentially, particle-fluid flows are ubiquitous in chemical processes involving intensive heat and mass transfer, and chemical reactions. Research has shown that such processes have several advantages; including, good mixing, uniform temperature field, and large particle-fluid contact area. Nevertheless, ideal comprehension of these processes is far from sufficient for safe operation, effective scale-up and innovation for energy efficient and sustainable developments. So far, it is evident that intensive heat and mass transfer between continuum fluids and discrete particulate materials plays a critical role in many chemical reactors. The residence and chemical reactions of particulate materials could span over hours, e.g. for rotary kilns and blast furnaces that proceed slowly while handling a huge amount of discrete solid materials. Consequently, CFD-DEM simulations of such processes need to consider a very long physical time to generate meaningful results. To understand and improve the operation of these reactors, discrete particle models are very helpful and computationally demanding.
Therefore, to overcome this shortfall, development of ideal viable methods to drastically reduce the computational time to an acceptable level for DEM-based simulation remains inevitable. On this account, Monash University in Australia researchers, Dr. Qinfu Hou, Dr. Dianyu E, Dr. Shibo Kuang and Professor Aibing Yu developed a new process scaling approach to reduce the computational cost for the combined CFD-DEM modelling of thermochemical behaviors in moving bed reactors. Their work is currently published in the research journal, Fuel Processing Technology.
In their approach, the scaled model was first derived based on the comprehensive consideration of the governing equations of mass, momentum and energy of two-phase flow. Specifically, the scaled CFD-DEM reactor model was developed based on the combined CFD-DEM approach, facilitated with validated heat and mass transfer, and chemical reaction models. This was realized through analysis of the governing equations in the dimensionless form and considering macroscopic heat and mass balance. Correspondingly, pertinent dimensionless numbers were identified from the dimensionless governing equations. Then, the researchers applied the scaled numerical model to a moving bed reactor, where different treatments and scaling correlations were tested with the scaled process parameters.
The authors found that in terms of flow, heat and mass transfer, and chemical reactions; the obtained results demonstrated significant acceleration of simulation that could be successfully achieved by the scaling approach, while as similar results could be generated with different scaling factors. In fact, it was noted that all the scaled models represented the same physical process but with lower computational costs.
In summary, the Australian study established a process scaling approach for CFD-DEM modelling of thermochemical behaviors in moving bed reactors. Different from other approaches, the scaled CFD-DEM model herein was applied to a moving bed reactor with two types of solid particles. Overall, the presented results in terms of flow, heat and mass transfer and chemical reactions demonstrated that two-order acceleration in computation could be successfully achieved by the process scaling approach. In a statement to Advances in Engineering, the authors mentioned that their research represents a critical step forward towards establishing virtual real-time thermochemical reactors with discrete particle models.
Qinfu Hou, Dianyu E, Shibo Kuang, Aibing Yu. A process scaling approach for CFD-DEM modelling of thermochemical behaviors in moving bed reactors. Fuel Processing Technology; volume 202 (2020) 106369.