A process scaling approach for CFD-DEM modelling of thermochemical behaviors in moving bed reactors


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.

About the author

Professor Aibing Yu specialized in process metallurgy, obtaining BEng in 1982 and MEng in 1985 from Northeastern University, China, PhD in 1990 from University of Wollongong and DSc in 2007 from the University of New South Wales, Australia. He is currently Pro Vice-Chancellor and President (Suzhou), Monash University, and Director of ARC Research Hub for Computational Particle Technology. He is a world-leading scientist in particle/powder technology and process engineering. He has authored/co-authored >1,000 publications (including >750 collected in the ISI Web of Science), delivered many invited plenary/keynote presentations at various international conferences, and graduated >40 postdoc fellows and >100 PhD students.

He is Executive Editor of Powder Technology, Regional Editor of Granular Matter, and on the editorial board of ~20 learned journals. He is a recipient of numerous prestigious awards and fellowships. He was elected to Fellow of the Australian Academy of Technological Sciences and Engineering in 2004, and Australian Academy of Science in 2011, and Foreign Academician of Chinese Academy of Engineering in 2017.

About the author

Dr Qinfu Hou is an Australian Research Council DECRA (Discovery Early Career Researcher Award) Fellow in the Department of Chemical Engineering of Monash University Australia. He was awarded a PhD in 2012 at UNSW Australia, ME and BE in 2003 and 2000 respectively at Northeastern University of China. Dr Hou has published 70+ articles with 1170+ citations and secured more than AUD$2M research funds.

Dr Hou has also received various awards in the past including ARC DECRA Fellow, reflecting the recognition at different stages, and been invited to give plenary/keynote talks at different international conferences. Aiming to formulate safe, smart, and sustainable energy-efficient processes involving granular materials, his research mission centres in unravelling fantastic mechanics and thermochemical behaviours of granular (and multiphase) flows through rigorous cutting-edge multiscale modelling techniques, experiments and theoretical analysis.

About the author

Dr Dianyu E is an Associate Professor in the China-Australia International Research Institute for Resources, Energy, Environment and Materials of Jiangxi University of Science and Technology of China. He was awarded a PhD in 2018 at Monash University Australia, ME and BE in 2010 and 2013 respectively at Liaoning/Beijing University of Science and Technology of China. His research has focused on the applications to a range of complex reactive flow processes in traditional and emerging industries particularly resource and energy sectors, including process metallurgy, biology processes, and renewable energy processes.

His research interests range from understanding fundamentals to optimizing and developing new, cleaner and more efficient technologies, powered by advanced multidimension and multiscale modelling techniques and experimental approaches.

About the author

Dr. Shibo Kuang obtained his Ph.D. in 2009 from School of Materials and Metallurgy, Northeastern University, China. In 2005, he as an exchange Ph.D. student joined SIMPAS which was established by Prof Aibing Yu at UNSW and later relocated to Monash University. Dr Kuang became a postdoctoral fellow in SIMPAS in 2010 and then a research fellow in 2015 and till now. His research has focused on the development and application of discrete- and continuum-based computer models to particle-fluid systems for gaining better process design and control, with special reference to particle transportation and separation as well as reacting multiphase flows.


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.

Go To Fuel Processing Technology

Check Also

3D-printed short carbon fibre reinforced perforated structures with negative Poisson's ratios: Mechanisms and design - Advances in Engineering

3D-printed short carbon fibre reinforced perforated structures with negative Poisson’s ratios