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Reviews in Chemical Engineering

Editor-in-Chief: Luss, Dan / Brauner, Neima

Editorial Board: Agar, David / Davis, Mark E. / Edgar, Thomas F. / Giorno, Lidietta / Joshi, J. B. / Khinast, Johannes / Kost, Joseph / Leal, L. Gary / Li, Jinghai / Mills, Patrick / Morbidelli, Massimo / Ng, Ka Ming / Schouten, Jaap C. / Seinfeld, John / Stitt, E. Hugh / Tronconi, Enrico / Vayenas, Constantinos G. / Zagoruiko, Andrey / Zondervan, Edwin

IMPACT FACTOR 2018: 4.200

CiteScore 2018: 4.96

SCImago Journal Rank (SJR) 2018: 1.016
Source Normalized Impact per Paper (SNIP) 2018: 1.572

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Volume 33, Issue 6


Discrete simulation of granular and particle-fluid flows: from fundamental study to engineering application

Wei Ge
  • Corresponding author
  • State Key Laboratory of Multiphase Complex Systems (MPCS), Institute of Process Engineering (IPE), Chinese Academy of Sciences (CAS), P. O. Box 353, Beijing 100190, China
  • University of Chinese Academy of Sciences, Beijing 100049, China
  • Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, China
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  • State Key Laboratory of Multiphase Complex Systems (MPCS), Institute of Process Engineering (IPE), Chinese Academy of Sciences (CAS), P. O. Box 353, Beijing 100190, China
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/ Qi Chang
  • State Key Laboratory of Multiphase Complex Systems (MPCS), Institute of Process Engineering (IPE), Chinese Academy of Sciences (CAS), P. O. Box 353, Beijing 100190, China
  • Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, China
  • School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
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/ Jinghai Li
  • State Key Laboratory of Multiphase Complex Systems (MPCS), Institute of Process Engineering (IPE), Chinese Academy of Sciences (CAS), P. O. Box 353, Beijing 100190, China
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Published Online: 2017-02-11 | DOI: https://doi.org/10.1515/revce-2015-0079


Multiphase chemical reactors with characteristic multiscale structures are intrinsically discrete at the elemental scale. However, due to the lack of multiscale models and the limitation of computational capability, such reactors are traditionally treated as continua through straightforward averaging in engineering simulations or as completely discrete systems in theoretical studies. The continuum approach is advantageous in terms of the scale and speed of computation but does not always give good predictions, which is, in many cases, the strength of the discrete approach. On the other hand, however, the discrete approach is too computationally expensive for engineering applications. Developments in computing science and technologies and encouraging progress in multiscale modeling have enabled discrete simulations to be extended to engineering systems and represent a promising approach to virtual process engineering (VPE, or virtual reality in process engineering). In this review, we analyze this emerging trend and emphasize that multiscale discrete simulations (MSDS), that is, considering multiscale structures in discrete simulation through rational coarse-graining and coupling between discrete and continuum methods with the effect of mesoscale structures accounted in both cases, is an effective way forward, which can be complementary to the continuum approach that is being improved by multiscale modeling also. For this purpose, our review is not meant to be a complete summary to the literature on discrete simulation, but rather a demonstration of its feasibility for engineering applications. We therefore discuss the enabling methods and technologies for MSDS, taking granular and particle-fluid flows as typical examples in chemical engineering. We cover the spectrum of modeling, numerical methods, algorithms, software implementation and even hardware-software codesign. The structural consistency among these aspects is shown to be the pivot for the success of MSDS. We conclude that with these developments, MSDS could soon become, among others, a mainstream simulation approach in chemical engineering which enables VPE.

Keywords: coarse-graining; discrete element method (DEM); discrete particle method (DPM); energy-minimization multiscale (EMMS) model; fluid-solid interaction; granular flow; heterogeneous computing; high-performance computing (HPC); mesoscale; multiphase flow; multiscale; nonspherical particle; particle-fluid flow; particle-in-cell (PIC); pseudo-particle modeling (PPM); smoothed particle hydrodynamics (SPH); supercomputing; virtual process engineering (VPE)


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About the article

Wei Ge

Wei Ge got his BSc in 1992 and his PhD in 1998, both from Harbin Institute of Technology, China. He has been a professor of chemical engineering at the Institute of Process Engineering, CAS, since 2006. He is engaged mainly in multiscale simulation of particle-fluid two-phase systems. He proposed pseudo-particle modeling and extended the EMMS model. As project leader, he developed the Mole series multiscale supercomputing systems to bridge simulation of molecular details to reactor performance. He is associate editor of Chem. Eng. Sci.

Limin Wang

Limin Wang got his PhD degree from Institute of Process Engineering (IPE), CAS, in 2008. From 2008 to 2009, he worked as a postdoctoral fellow in CNRS, France. He has been a professor of chemical engineering at the Institute of Process Engineering, CAS, since 2016. He is engaged mainly in mesoscale concept for turbulence modeling and simulation, lattice Boltzmann modeling for particle-fluid two-phase flows, and lattice- and particle- based methods for complex flows.

Ji Xu

Ji Xu got his BSc in 2006 from Xi’an Jiaotong University and his PhD in 2012 from Institute of Process Engineering (IPE), CAS. He has been an associate professor of chemical engineering at IPE since 2015. He is engaged mainly in developing supercomputing methods for large-scale particle simulations, for example MD and DEM.

Feiguo Chen

Feiguo Chen got his BSc in 2002 from Tsinghua University and his PhD in 2009 from CAS. He has been an associate professor of chemical engineering at Institute of Process Engineering, CAS, since 2012. He is engaged mainly in multiscale discrete simulation for multiphase systems.

Guangzheng Zhou

Guangzheng Zhou got his PhD in 2010 from Institute of Process Engineering, CAS. He is engaged mainly in mesh-free simulation of granular flows and liquid-liquid two-phase flows. He designed some novel baffles based on DEM for the enhancement of powder mixing in tumbling blenders. He also proposed a revised model of surface tension based on SPH and revealed the inherent non-Newtonian properties of noncompressible SPH.

Liqiang Lu

Liqiang Lu got his PhD in 2016 from Institute of Process Engineering, CAS. His research focuses on large-scale discrete particle simulation of fluid-particle systems using OpenFOAM and GPU-based DEM code. He proposed the EMMS-DPM coarse grained method for simulation of gas-solid flows using EMMS model and KTGFs. He is also interested in code optimization on Xeon Phi and GPUs and developed an online interactive gas solid flow simulation system. Since March 2016, he has been working as an ORISE postdoctoral researcher at the NETL Multiphase Flow Science Team, USA.

Qi Chang

Qi Chang received his BSc and MSc in chemical engineering and technology from Tianjin University in 2009 and 2013, respectively, and is now pursuing his PhD study there and a visiting student at IPE now. He is now working on DNS of particle fluid flows.

Jinghai Li

Jinghai Li established the EMMS model for gas-solid systems and generalized it into the EMMS paradigm of computation. He devotes himself to promoting mesoscience based on the EMMS principle of compromise in competition as an interdisciplinary science. He is vice president of the International Council for Science, vice chairman of the China Association of Science and Technology, and vice president of the Chinese Society of Chemical Engineering. He is editor-in-chief of Particuology. He holds memberships with CAS, TWAS, SATW, RAEng, and ATSE.

Received: 2015-12-25

Accepted: 2016-11-28

Published Online: 2017-02-11

Published in Print: 2017-11-27

Citation Information: Reviews in Chemical Engineering, Volume 33, Issue 6, Pages 551–623, ISSN (Online) 2191-0235, ISSN (Print) 0167-8299, DOI: https://doi.org/10.1515/revce-2015-0079.

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