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Footprint and Philosophy

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From Multiscale Modeling to Meso-Science

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Abstract

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.

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Abbreviations

\( C_{\text{d}} \) :

Drag coefficient, dimensionless

d cl :

Cluster diameter, m

d p :

Particle diameter, m

\( E_{\text{j}} \left( {\mathbf{x}} \right) \) :

Objective function with respect to dominant mechanism j

\( E_{\text{OH}} \) :

Hydrophilic potential in unit volume, m2/s3

\( E_{\text{WT}} \) :

Lipophilic potential in unit volume, m2/s3

\( E_{\text{s}} \) :

Surface energy in unit area, m2/s3

\( E_{{{\upmu}}} \) :

Viscous dissipation rate in unit volume, m2/s3

F i :

Constraints condition i

f :

Volume fraction of dense phase, dimensionless

\( g \) :

Gravitational acceleration, m/s2

\( H \) :

The height of the bed, m

\( H_{\text{a}} \) :

Potential a in unit volume, m2/s3

\( H_{\text{b}} \) :

Potential b in unit volume, m2/s3

\( L \) :

Characteristic length of flow, m

\( N_{\text{surf}} \) :

Rate of energy dissipation due to bubble breakage and coalescence per unit mass, W/kg

\( N_{\text{st}} \) :

Rate of energy dissipation for transporting and suspending particles per unit mass, W/kg

\( N_{\text{turb}} \) :

Rate of energy dissipation in turbulent liquid phase per unit mass, W/kg

\( R \) :

Pipe radius, m

\( Re \) :

Reynolds number, dimensionless

\( r \) :

Radial coordinate, m

U c :

Gas in the dense phase superficial velocity, m/s

U f :

Gas in the dilute phase superficial velocity, m/s

U pc :

Solid in the dense phase superficial velocity, m/s

U pf :

Solid in the dilute phase superficial velocity, m/s

\( W_{\text{st}} \) :

Energy consumption for transporting and suspending particles in unit volume, W/m3

\( \bar{W}_{\rm v} \) :

Viscous shear dissipation rate in unit volume, W/m3

\( \bar{W}_{\text{te}} \) :

Turbulent dissipation rate in unit volume, W/m3

X :

State parameter

\( S \) :

Surface energy in unit volume, m2/s3

\( Sh \) :

Sherwood number, dimensionless

\( \varepsilon \) :

Local average voidage, dimensionless

ε c :

Voidage in dense phase, dimensionless

ε f :

Voidage in dilute phase, dimensionless

\( \varphi_{\rm r} \) :

Dissipation rate of unit amount of kinetic energy across unit length, m2/s3

\( \eta \) :

Kolmogorov microscales, m

\( \rho \) :

Density, kg/m3

a:

Index of particle a

b:

Index of particle b

c:

Dense phase

f:

Dilute phase or fluid

g:

Gas

mb:

Minimum bubble

mf:

Minimum fluidization

p:

Particle

s:

Solid

CFB:

Circulating fluidized bed

CFD:

Computational fluid dynamics

CPU:

Central processing unit

CUDA:

Compute unified device architecture

EMMS:

Energy-minimization multiscale

FD:

Fluid-dominated

GPU:

Graphics processing unit

MOV:

Multi-objective variational

PD:

Particle-dominated

PFC:

Particle-fluid compromising

TFM:

Two-fluid model

VPE:

Virtual process engineering

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Authors and Affiliations

  1. Institute of Process Engineering, Chinese Academy of Sciences, Zhongguancun North Second Street 1, Beijing, 100190, People’s Republic of China

    Jinghai Li, Wei Ge, Wei Wang, Ning Yang, Xinhua Liu, Limin Wang, Xianfeng He, Xiaowei Wang, Junwu Wang & Mooson Kwauk

Authors
  1. Jinghai Li
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  2. Wei Ge
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  3. Wei Wang
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  4. Ning Yang
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  5. Xinhua Liu
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  6. Limin Wang
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  7. Xianfeng He
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  8. Xiaowei Wang
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  9. Junwu Wang
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  10. Mooson Kwauk
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Correspondence to Jinghai Li .

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Li, J. et al. (2013). Footprint and Philosophy. In: From Multiscale Modeling to Meso-Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35189-1_1

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  • DOI: https://doi.org/10.1007/978-3-642-35189-1_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35188-4

  • Online ISBN: 978-3-642-35189-1

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