from massalski to micress and beyond: an introduction to

From Massalski to MICRESS and beyond: An introduction to

MICRESS and current trends in Integrated Computational

Materials Engineering “ICME”

Dr. rer.nat. Georg J. Schmitz

Version August 2014

First Edition 1986

ca. 1980: first PCs

8086- Processors

about 1960

about 1980:

first networks / Internet

1973: my first calculator (DM 300,--) …150 €

thermodynamic databases are NOT (!!) just

collections of experimental data in an Excel sheet !!

Thermodynamic databases are based on physical models allowing

extrapolations into „unknown areas“

0

10

20

30

40

1 2 3 4 5 6 7

y

x

parabolaexample:

y-y0 = a(x-x0)2

here: y0=1 a=1 x0=0

xs

m

ideal

mmm GGGG 0

i

i

SER

mm TdTcTbTaHG )ln(

o

BB

o

AAm GxGxG 0

BBAA

ideal

m xxxxRTG lnln

0

, )(k

k

BABA

k

BA

xs

m xxLxxG

....)()( 2

,

2

,

1

,

0

BABABABABABA xxLxxLLxx

The CALPHAD method

CALculation of PHAse Diagrams

Models for the thermodynamic properties

of each phase G(T, P, y)

Database for model parameters

Predictive calculation of:

thermodynamic properties

equilibrium states

phase diagrams

Fundamental

theories

Empirical

rulesExperimental

Information

www.calphad.org

1969 Formation of CALPHAD.

1971 Sub-lattice model for 2

comp. (Hillert and

Steffansson, KTH).

1977 Development of

Thermo-Calc starts

Database for Model

Parameters

http://www.calphad.org/

•

•

•

•

•

•

•

•

•

•

•

•

Tsol~ 1240 °C

Tliq ~ 1410°C

Fe-4Cr-8Mo-2V-0.3Mn-0.3Si-1C

The CALPHAD method

CALculation of PHAse Diagrams

Models for the thermodynamic properties

of each phase G(T, P, y)

Database for model parameters

Predictive calculation of:

thermodynamic properties

equilibrium states

phase diagrams

Fundamental

theories

Empirical

rulesExperimental

Information

www.calphad.org

1969 Formation of CALPHAD.

1971 Sub-lattice model for 2 comp.

(Hillert and Steffansson, KTH).

1977 Development of Thermo-Calc

starts

2007

1986

http://www.calphad.org/

possible

Not available

Determination of phase fractions

Prediction of onset of precipitate formation

Determination of temperatures for phase transitions

Estimation of solidification behaviour

Determination of thermodynamic data

Information on kinetics

Information on microstructure

Information about materials properties

Al

Mo

Cr

),,(ln PTxfRTMB

Diffusion without a chemical gradient:

- Tracer diffusion coefficients

Diffusion under a chemical gradient:

- Chemical interdiffusion coefficients

- Intrinsic diffusion coefficients

Logarithm of the Atomic Mobility for

Individual Elements

Applications

~

D

0

0.02

0.04

0.06

0.08

0.1

0.12

-1000 -500 0 500 1000

Ma

ss F

ract

ion

Distance (m)

Cr

Co

W

Ta

Al

Ti

Mo

Re

HfNb

René-N4 René-N5

g g

6.35 mm 6.35 mm

Double geometric grid: 200 points

Experimental work performed by T. Hansen, P. Merewether, B.

Mueller, Howmet Corporation, Whitehall, MI.

From: C. E. Campbell, Metallurgy Division, NIST

D is a 10×10 matrix where all coefficients

depend on concentration

René-N4/René-N5 at 1293 °C for 100 h

Databases used

Thermodynamics: ThermoTech

Kinetics: NIST Ni-mob

possible

still not available






Information on kinetics (diffusion)



www.micress.de

van der Waals (1893)

Korteweg (1901)

Landau-Ginzburg (1950)

Cahn-Hilliard (1958)

Halperin, Hohenberg & Ma (1977)

Langer (1978) phase field

Fix, Caginalp (1986) phase field

Kobayashi (1992) dendrites with phase field

Steinbach (1996) multi-phase-field-model

Elder (2002) phase-field crystal models

2010 Physica D 94 (1996)135

The phase-field equation(s) .....an own area of research

ss2

ssss

2

s 11211

t,x

G

Stabilise

- +

Move Smooth

~t,x

~T t,x

~c t,x

cT ,dG

t,x

t,x

200 µm

r = 3 µm

4cos(0 1

Stabilise

- +

Move Smooth

ss2

ssss

2

s 11211

t,x

G

4cos(0 1

cited > 300 times (status Feb 2014)

one phase field for each phase: L+ + g= 1

Basic ideas: (see I.Steinbach et al. Physica D 94 (1996) 135)

definition of one phase field for each phase AND for each grain of a phase

pairwise interaction for each pair of phases/grains like in standard phase-field

possibility of implementation of specific phase/grain boundary properties

Specific aspects:

1D-simulation unable to reproduce multi-

phase interactions

physics of triple junctions

Further concepts:

coupling to thermodynamic databases

coupling to mobility databases

mobility

database

Use of Thermodynamic Data in MICRESS®

multicomponent diffusion solver

M I C R E S S ®

nucleation model

temperature solver

multiphase-field solver

time loop

Thermo-Calc

CALPHAD database )GwK()t,x(

?TT c ritu n d

cD)t,x(c

possible

still not available









Information about properties of component

Cluster of Excellence

Integrative Production Technologies for

High Wage Countries

Virtual Process Chains for Processing of

Materials

Speakers:

Dr.-Ing. Ulrich Prahl

Dr. rer.nat. Georg J. Schmitz

Seite 42 © RWTH Aachen University staff involved (2013):

about 30 scientists (8 scientists full time equivalent)

Virtual Process Chains for Processing of Materials

Scopes

integrative virtual description of processes and microstructure evolution along the production chain

prediction of effective materials properties from calculated microstructures

interfacing between microstructure simulations and macroscopic process simulations

virtual documentation of the product history towards life cycle modelling

verification for different test-cases of scientific and economic interest

- casting - solidification - hot forming - cold forming - heat treatment - joining - coating -

Seite 43 © RWTH Aachen University

Example of a process chain

co

mp

on

en

t m

ikro

s

ub

-µ

rolling forging carburizing welding cooling

Integration along process chain

heating

averaged

properties

boundary

conditions

precipitates

Grain growth


Numerical tensile tests

200

400

600

800

1000

1200

1400

0,00 0,02 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18 0,20

true strain

tru

e s

tre

ss (

MP

a)

20%

+5%

-5%

Amount of martensite: 20% +/-5

Annealing temperature: 740°C

FE Simulation

Experiments

Numerical tensile tests of a simulated

microstructure (DP600 steel) by means

of RVE-FE and experimental bulge test

show good agreement

PHD Thesis

C. Thomser IEHK RWTH Aachen (2009)


Crack propagation in virtual microstructure


Effective properties

RVE: pearlite in ferrite matrix

U-O-forming simulation of

a pipeline tube

equivalent plastic

microstrain

localization in critical

regions:

applying local macrostrains

on the RVE

virtual test/

homogenization

effective anisotropic

flow curves

Ferrite-Cementite

bilamella


…Integrated Computational Materials Engineering „ICME“….

appeared in April 2012

ISBN-10: 3-527-33081-X

ISBN: 978-3-527-33081-2

to appear in Chinese language

edition in August 2016

www.icmeg.eu

The Integrated Computational Materials Engineering expert group

- EU project ICMEg -

www.icmeg.eu

www.icmeg.info

consortium: 11 partners, 6 countries vision: plug&play in ICME

approach: global, open standards How to do in practice? Read more:

Possible/in reach

still not available









Information about properties of component

Life cycle modelling

Inverse modelling

Adv.Eng.Materials

2006

Adv.Eng.Materials

2009

Int. J. Mater Res.

2010

Adv.Eng.Materials

2003

Thank you very much for your attention!

www.micress.de www.thermocalc.de

www.thermocalc.se

from massalski to micress and beyond: an introduction to

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