???? ?? Multiscale simulation for process development [Ch. 2] in Computational multiscale modeling of fluids and solids by M.O. Steinhauser - PowerPoint PPT Presentation

About This Presentation
Title:

???? ?? Multiscale simulation for process development [Ch. 2] in Computational multiscale modeling of fluids and solids by M.O. Steinhauser

Description:

Multiscale simulation for process development [Ch. 2] in Computational multiscale modeling of fluids and solids by M.O. Steinhauser – PowerPoint PPT presentation

Number of Views:33
Avg rating:3.0/5.0
Slides: 10
Provided by: Limnot
Category:

less

Transcript and Presenter's Notes

Title: ???? ?? Multiscale simulation for process development [Ch. 2] in Computational multiscale modeling of fluids and solids by M.O. Steinhauser


1
???? ??Multiscale simulationfor process
developmentCh. 2in Computational multiscale
modeling of fluids and solids by M.O. Steinhauser
  • Major Interdisciplinary program of the
    integrated biotechnology
  • Graduate school of bio- information technology
  • Youngil Lim (N110), Lab. FACS
  • phone 82 31 670 5207 (direct)
  • Fax 82 31 670 5445, mobile phone 82 10 7665
    5207
  • Email limyi_at_hknu.ac.kr, homepage 
    http//facs.maru.net

2
Ch. 2. Multiscale computational material science
  • Time and space
  • Four-dimensional space-time
  • Isaac Newtons Principia (1687) physical
    modeling of the world (calculus differential
    equation with time and space)
  • Max Plancks Quantum theory (1900)
  • Einsteins Principle of general relativity (1916)

3
Ch. 2.2 Material science in the scale
4
Ch. 2.2 Material science on multiscale
Reducing Degree of Freedom
Length 12 orders of magnitude (100 1012 )
  • Instruments
  • TEM (Transmission Electron Microscope)
  • - resolution 0.2nm
  • SEM (Scanning Electron Microscope)
  • - resolution 10nm
  • Fig. 2.1 (p32, Steinhauser, 2007).

5
Ch. 2.3 Modeling
Model equation Newtons classical mechanics
(continuum-based modeling) - macroscopic
state variables T, P, V, S, F, G, ?, ?ij -
state variables are expressed as functions of x,
y, z, and t. Quantum theory (discrete atom
modeling) - position (r), momentum of
molecules
Fig. 2.6. Galileis method (1638) of using
experiments to test idealizations of
theories which in turn are based on abstract
mathematical principles
  • Fig. 2.6 (p38, Steinhauser, 2007).

6
Ch. 2.4.2 Structure property paradigm
Microscopic structure determines macroscopic
properties
  • Table 2.1 (p47, Steinhauser, 2007).

7
Ch. 2.4.4 Numerical modeling and simulation
Microscopic structure determines macroscopic
properties
  • Fig. 2.9 (p56, Steinhauser, 2007).

8
Ch. 2.4.5 Unification of physical theories
Reductionism in physics
Einstein (1916)
Dirac (1931)
Plank (1900)
Newton (1687)
4 fundamental forces - weak interaction on
quarks - strong interaction on atomic nuclei -
electron-magnetic interaction on charged
particles - gravitational interaction between
astronomic objects
- Which force is the weakest ? - First-principles
electro-magnetic gravity forces - ab
initio quantum theory
  • Fig. 2.10 (p57, Steinhauser, 2007).

9
Application of MSS (multi-scale simulation)to
p-xylene SMB process development
  • Ustinov and Do (2004), Application of density
    functional theory (DFT) to analysis of energetic
    heterogeneity and pore size distribution of
    activated carbons, Langmuir, 20, p3791-3797.
Write a Comment
User Comments (0)
About PowerShow.com