Xianfeng He

From Multiscale Modeling to Meso-Science

Multiscale modeling is becoming essential for accurate, rapid simulation in science and engineering. This book presents the results of three decades of research on multiscale modeling in process engineering from principles to application, and its generalization for different fields. This book considers the universality of meso-scale phenomena for the first time, and provides insight into the emerging discipline that unifies them, meso-science, as well as new perspectives for virtual process engineering. Multiscale modeling is applied in areas including: multiphase flow and fluid dynamicschemical, biochemical and process engineeringmineral processing and metallurgical engineeringenergy and resourcesmaterials science and engineeringJinghai Li is Vice-President of the Chinese Academy of Sciences (CAS), a professor at the Institute of Process Engineering, CAS, and leader of the EMMS (Energy-minimizing multiscale) Group. Wei Ge, Wei Wang, Ning Yang and Junwu Wang are professors at the EMMS Group, part of the Institute of Process Engineering, CAS. Xinhua Liu, Limin Wang, Xianfeng He and Xiaowei Wang are associate professors at the EMMS Group, part of the Institute of Process Engineering, CAS. Mooson Kwauk is an emeritus director of the Institute of Process Engineering, CAS, and is an advisor to the EMMS Group.

Petascale molecular dynamics simulation of crystalline silicon on Tianhe-1A

An efficient and highly scalable bond-order potential code has been developed for the molecular dynamics simulation of bulk silicon, reaching 1.87 Pflops (floating point operations per second) in single precision on 7168 graphic processing units (GPUs) of the Tianhe-1A system. Furthermore, by coupling GPUs and central processing units, we also simulated surface reconstruction of crystalline silicon at the sub-millimeter scale with more than 110 billion atoms, reaching 1.17 Pflops in single precision plus 92.1 Tflops in double precision on the entire Tianhe-1A system. Such simulations can provide unprecedented insight into a variety of microscopic behaviors or structures, such as doping, defects, grain boundaries, and surface reactions.

Partial Realization of the EMMS Paradigm

This chapter uses the top-down mode of the EMMS paradigm on CPU clusters to realize structural similarity between problem, model, and software, but not hardware. First we propose a set of structure-dependent conservation equations based on the structure of the problem. A computing scheme is then realized by integrating EMMS drag into the reduced SFM; that is, EMMS-based multi-fluid modeling (EFM). In this process, the structure of both model and software (coding) is consistent with that of the investigated multiscale problem. Simulation with the EFM starts with the global prediction of the macro-scale distribution. Using this as an initial condition greatly reduces the time needed to reach a steady state. Time-dependent, regional evolution is then simulated; its accuracy is guaranteed because of the meso-scale modeling of both drag and mass transfer coefficient. Extensive application of the EMMS paradigm identifies advantages over conventional computational fluid dynamics (CFD) approaches such as higher accuracy and efficiency. Complete realization of the EMMS paradigm with consistent hardware will be discussed in Chap. 7.

Footprint and Philosophy

This chapter summarizes the footprint, philosophy and strategy of this book. The historical evolution of the energy minimization multiscale (EMMS) model is briefly introduced; the structure of the book is also outlined. To introduce the philosophy of this book, the spectrum of science and technology and the common multiscale nature of different disciplines are discussed. As meso-scales are identified as the critical issue in understanding complex systems, three such levels (material, reactor and system) in process engineering are analyzed in detail, emphasizing the importance of compromise between dominant mechanisms in generating meso-scale phenomena. Finally, the footprint of the EMMS model from a simple idea to a computational paradigm (the EMMS paradigm), and further to meso-science, is outlined to complete the overview of this book.

Applications of EMMS Drag in Industry

This chapter reviews the use of the EMMS drag and paradigm to solve industrial problems including the design, optimization and scale-up of the fluid catalytic cracking (FCC) process, and optimization of fluidized bed combustion and Fischer-Tropsch (FT) synthesis. Application of the EMMS drag to these problems in turn aids its development.

Meso-Scale Modeling: The EMMS Model for Gas-Solid Systems

This chapter introduces the EMMS model for gas-solid two-phase flow and the motive for this series of work. The EMMS model focuses on the meso-scale phenomenon of particle clustering, correlating it to the micro-scale of single particles and the macro-scale of the vessel operating conditions, material properties, and boundary conditions by analyzing the compromise between dominant mechanisms to define the meso-scale stability condition. The EMMS model can be solved for the eight parameters that describe the meso-scale structure and capture the so-called choking and drag-reduction phenomena in gas-solid fluidization systems, and further enables the intrinsic regime, operation diagram and overall fluid dynamics of systems to be determined. This chapter provides a solid basis to integrate the EMMS model with computational fluid dynamics (CFD) simulations and develop the EMMS paradigm.

Extension of the EMMS Model to Gas-Liquid Systems

The Dual-Bubble-Size (DBS) model is an extension of the energy minimization multiscale (EMMS) approach for gas-liquid systems. The system is resolved into a liquid phase, small bubbles and large bubbles, and is jointly dominated by two movement tendencies; i.e., those of the small and large bubbles. A stability condition is formulated to reflect the compromise between these dominant mechanisms, offering another constraint in addition to mass and momentum conservation equations. The DBS model can theoretically predict the regime transition in bubble columns and physically explain the macro-scale evolution of flow structures through the jump change in the global minimum of the micro-scale energy dissipation changing from one point to another within the model space of the structure parameters. The DBS model is found to be an intrinsic model for gas-liquid systems in contrast to the models for single, triple, and multiple classes of bubble. A new model for the ratio of drag coefficient to bubble diameter, that is, the EMMS drag, is then integrated into the Eulerian-Eulerian computational fluid dynamics (CFD) models. The resulting improved prediction demonstrates the ability of the DBS model to reveal the multiscale nature and complexity of gas-liquid systems.

Perspectives: Meso-Science and Virtual Process Engineering

Summarising the whole book, this chapter gives perspectives, derived from the EMMS research, on future directions, particularly, emphasizing the possibility of meso-science and the realization of VPE. The discussion here is limited to author’s capacity of knowledge and current understandings, only aiming at triggering further discussion in chemical engineering and beyond.

Academic Applications of EMMS Drag

Parallel to its extension and industrial application, the EMMS approach has received increasing attention from academia with applications in computational fluid dynamics (CFD) simulations. Following the first publication combining the EMMS drag with CFD simulation, the fluidization community quickly recognized the significance of this method. EMMS-based methods have since been applied to various branches of fluidization. In turn, these academic applications under various conditions contributed to the verification and further development of EMMS model. This chapter provides a general overview of the academic applications of EMMS drag, highlighting several representative studies. In these studies, EMMS modeling was extended from simulations of systems with low solid flux to those with high solid flux, from modeling of Geldart group A particles to those of group B, and from gas-solid to gas-liquid and other complex systems. The model itself was also developed extensively, for example, by the constitutive formula for cluster diameter.

Experimental Characterization of Meso-Scale Processes

Meso-scale structures possess spatio-temporal dynamic heterogeneity, which requires fine space and time resolutions of quantifying parameters to be fully understood. The EMMS group has been focusing on numerical simulation and experimental characterization of multiscale processes in multi-phase complex systems since the 1980s. This chapter introduces several experimental and measurement technologies developed or extended by the EMMS group to quantitatively characterize meso-scale processes and particle clustering dynamics as well as their effects on transport properties in gas-solid systems. These technologies have allowed the EMMS theory to be experimentally validated and facilitated the construction of a rudimentary platform for virtual process engineering (VPE).