공정개발을 위한 다중규모 모사

Multiscale simulation for process development[General introduction]

Major: Interdisciplinary program of the integrated biotechnology

Graduate school of bio- & information technology

Youngil Lim (N110), Lab. FACSYoungil Lim (N110), Lab. FACSphone: +82 31 670 5207 (direct)phone: +82 31 670 5207 (direct)

Fax: +82 31 670 5445, mobile phone: +82 10 7665 5207Fax: +82 31 670 5445, mobile phone: +82 10 7665 5207Email: Email: limyi@hknu.ac.kr, homepage:, homepage:   http://facs.maru.net

Some key words

- Multi-scale ?

- Multi-phase ?

- Multi-component ?

- Multi-physics ?

- Multi-scale simulation for process development?

Some examples

- Micro- and macro-transport in porous media of adsorption column

- CFD, PBE, and CKM in fluidized-bed for solar-grade poly-silicon production

- Cells, proteins, peptides, amino acid, molecules, atoms and electrons

- Multiscale modeling in product engineering

Preface 1In recent years we have seen an explosive growth of activities in multiscale

modeling and computation, with applications in many areas including material

science, fluid mechanics, chemistry, and biology. Relevant examples of

practical interest include: structural analysis of materials, flow through porous

media, turbulent transport in high Reynolds number flows, large-scale

molecular dynamic simulations, ab-initio physics and chemistry, and a

multitude of others.

Though multiple scale models are not new, the topic has recently taken on a new

sense of urgency. A number of hybrid approaches are now created in which

ideas coming from distinct disciplines or modeling approaches are unified to

produce new and computationally efficient techniques.

M. O. Steinhauser, Computational multiscale modeling of fluids and solids, Springer, 2008.

Preface 2Traditional approaches to modeling focus on one scale. If our interest is the macroscale behavior of a

system in an engineering application, we model the effect of the smaller scales by some

constitutive relations. If our interest is in the detailed microscopic mechanism of a process. We

assume that there is nothing ineresting happening at the larger scales. For example, that the

process is homogeneous at larger scales.

Take the example of solids. Engineers have long been interested in the macroscale behavior of solids.

They use continuum models and represent atomistic effects by constitutive relations. Solids state

physicists, however, are more interested in the behavior of solids at the atomic or electronic level,

often working under the assumption that the relevant processes are homogenous at the

macroscopic scale. As a result, engineers are able to design structures and bridges without

acquiring much understanding about the origins of the cohesion between the atoms in the material.

Solid state physicists can provide such an understanding at a fundamental level. But they are

often quite helpless when faced with a real engineering problem.

E. Weinan, Principles of multiscale modeling, Cambridge Univ. Press, 2011.

Multiscale Modeling and its Application to Catalyst Design and Portable Power Generation, Prof. Dion G. Vlachos

(University of Delaware, vlachos@udel.edu, www.che.udel.edu/vlachos)

Multiscale simulation is emerging as a new scientific field in chemical, materials, and

biological sciences. The idea of multiscale modeling is straightforward: one computes

information at a smaller (finer) scale and passes it to a model at a larger (coarser) scale by

leaving out degrees of freedom as one moves from finer to coarser scales.

The obvious goal of multiscale modeling is to predict macroscopic behavior of an

engineering process from first principles (bottom-up approach). However, the emerging

fields of nanotechnology and biotechnology impose new challenges and opportunities

(top-down approach). For example, the miniaturization of microchemical systems for

portable and distributed power generation imposes new challenges and opportunities than

the conventional scaling up chemical engineers have worked on.

Course # Course name Time Room #

  Multiscale simulation for process development Thu. 9-12시 N116

Overview

Multiscale simulation is emerging as a new scientific field in chemical, materials, and biological sciences. The idea of multiscale modeling is straightforward: one computes information at a smaller (finer) scale and passes it to a model at a larger (coarser) scale by leaving out degrees of freedom as one moves from finer to coarser scales.In recent years we have seen an explosive growth of activities in multiscale modeling and computation, with applications in many areas including material science, fluid mechanics, chemistry, and biology. Relevant examples of practical interest include: structural analysis of materials, flow through porous media, turbulent transport in high Reynolds number flows, large-scale molecular dynamic simulations, ab-initio physics and chemistry, and a multitude of others.In this lecture, we learn a multiscale simulation (MSS) approach which includes MLS (molecular-level simulation), mFLS (micro-fluid-level simulation) as well as FLS (fluid-level simulation), describing how to obtain model parameters and design factors required for process development from FLS, mFLS, and MLS. Specifically, the MSS approach is applied to process modeling and development, especially, adsorption process and fluidized-bed process.

Method   Lecture(O), Seminar (O), Computational practice (O),  Factory tour (-), Beam projector(O)

Evaluation   Attendance: 8%,  homework: 22%,  Mid-exam: 30%,  Final-exam: 40%, Presentation: 0%

Textbook- Principles of multiscale modeling, E. Weinan, Cambridge Univ. Press, 2011.- Computational multiscale modeling of fluids and solids, M. O. Steinhauser , Springer, 2008.

Outline

Objectives of this lecture

We learn a multiscale simulation (MSS) approach which includes MLS

(molecular-level simulation), mFLS (micro-fluid-level simulation) as well as

FLS (fluid-level simulation), describing how to obtain model parameters and

design factors required for process development from FLS, mFLS, and MLS.

Specifically, the MSS approach is applied to process modeling and

development of adsorption and fluidized-bed.

Lecture contentsA MSS approach is applied for process modeling and development to adsorption and fluidized-bed processes. MSS for process development is classified into MLS, mFLS, FLS, and PLS and connectivity between them is identified. -PLS (Process-level simulation)For adsorption process, adsorption isotherms are obtained from MLS, and it will be found whether axial dispersion coefficient and mass transfer coefficient can be predicted from mFLS. CFD (computational fluid dynamics) in FLS is performed to understand flow dynamics inside adsorption columns and to identify optimal design parameters for process. For fluidized-bed processes such as BFB (bubbling fluidized-bed) and DFB (dual fluidized bed), process modeling and CFD simulation are carried out and it will be investigated how to get their model parameters from MLS and mFLS. -FLS (Fluid-level simulation)CFD simulation is performed for adsorption and fluidized-bed processes to identify optimal design factors and operating conditions. Connectivity of FLS to PLS, MLS, and mFLS is studied.-mFLS (Micro-fluid-level simulation)Using LBM (lattice-Boltzmann method) for fluid dynamics in micro-pore networks, we will examine the effects of pore mouth, and predict effective diffusivity and effective mass transfer rate of an absorbate.-MLS (Molecular-level simulation)Adsorption isotherms on zeolite or an adsorbent is predicted at a high pressure and temperature, combining GCMC (grand canonical Monte Carlo) often used for molecular simulation of adsorption

Week Contents Remarks

1 Introduction (Multiscale simulation for process development)  Two text books.

2 Example 1: Multiscale modeling in fluidized-bed for solar-grade poly-silicon production  Balaji et al. (Powder Technol., 2010)

3 Example 2: Micro- and Macro- transport in porous media of adsorption column (Lattice-Boltzmann approach)  Verma et al., (Chem. Eng. Sci., 2007)

4 Example 3: Multiscale simulation in product engineering Jaworski and Zakrzewska (Comput. Chem. Eng., 2011)

5 Ch1. Introduction (Computational multiscale modeling of fluids and solids) Steinhauser (2008)

6 Ch2. Multiscale computational material science(Computational multiscale modeling of fluids and solids) Steinhauser (2008)

7 Ch7. Computational methods on mesoscopic/macroscopic scale(Computational multiscale modeling of fluids and solids) Steinhauser (2008)

8 Mid-term exam.

9 Ch1. Introduction (Principles of multiscale modeling) Weinane (2011)

10 Ch2. Analytical methods (Principles of multiscale modeling) Weinane (2011)

11 Ch4. The hierarchy of physical models 1 (Principles of multiscale modeling) Weinane (2011)

12 Ch4. The hierarchy of physical models 2 (Principles of multiscale modeling) Weinane (2011)

13 LBM (lattice-Boltzmann method) for mFLS

14 Overview of MLS, mFLS, FLS and PLS  

15 Final exam.  

Weekly Lecture Plan

Fluid dynamics in pores

Baralla et al (2001), A computer-aided model to simulate membrane fouling processes, Sep. & Pur. Tech., 22-23, 489-498.

25 Å,~10-9 m

300 m,~10-4 m

Unit cell Macro-pore Resin particle Column100 1000 1000

1000 Å,~10-7 m

10 cm,~0.1 m

Multiscale simulation in adsorption process

Table 1.2. Annual research objectives (Lim, 2011, Project proposal, funded by NRF, Korea.)

Year Objectives Remarks Objectives diagram

1st Year(2011-2012)

Understanding of individual scale simulation methods (MLS, mFLS, FLS, and PLS)

- Continuum phase: CFD (computational fluid dynamics)- Discrete phase: MD (molecular dynamics)- Continuum-discrete phase: LBM (lattice Boltzmann method)

 

2nd year(2012-2013)

Connectivity between two levels (MLS-mFLS, mFLS-FLS, and FLS-PLS).

-To obtain the process model parameters from simulation in other scales.- MSS is applied to adsorption and fluidized-bed processes

 

3rd year(2013-2014)

Application to adsorption and fluidized-bed processes

- To integrate all the scales for process development and simulation  

MLS (molecular level simulation), mFLS (micro-fluid level simulation), FLS (fluid level simulation), PLS (process level simulation).

Table 3.1 Outline of research subjects and methodsSubjects MLS mFLS FLS PLS

Dimension 3D 2D or 3D 2D or 3D 1D

Spatial scale 2×10-9 m 100×10-6 m 1×10-3~2×100 m 2×100 m

Physical/thermodynamic properties

adsorption isothermsheat of adsorptionpore diffusivityparticle densitypore size distibutiontotal pore volumepore wall surfaceConnolly surface areaporosity

 

axial diffusivityradial diffusivityfluid densityheat capacityadsorption isotherms

mass transfer coefficientaxial diffusivityadsorption isothermsbed voidage 

Zeolites(adsorbents)

Molecular structure MS* Forcite      

Physical properties MS Forcite      

Adsorption isotherms MS Sorption      

Diffusion coefficient MS Forcite Plus      

Zeolite-Fluid interaction

High-pressure effects   micro-flow dynamics    

Fluid flow in pore   micro-flow dynamics    

Fluid-Process interaction

Fluid dynamics in column     Fluent/ComSol  

Column geometry effects     Fluent/ComSol  

mass transfer effects     Fluent/ComSol  

Pressure drop     Fluent/ComSol  

Process

Dead-zone treatment       FAST-Chrom/SMB

Operating condition optimization       FAST-Chrom/SMB

Design parameter optimization       FAST-Chrom/SMB

Process design       ASPEN Chromatography