multiscale materials modeling for metal additive … of the future/3d... · a material modeling...

Anssi Laukkanen, Tom Andersson, Tatu Pinomaa, Matti Lindroos, Merja Sippola, Sami Majaniemi, Tomi Suhonen (et al.++) VTT Materials & Manufacturing, Finland 22.11.2016

Multiscale Materials Modeling for Metal Additive Manufacturing

01/12/2016 2

Brief introduction to multiscale materials modeling & Integrated

Computational Materials Engineering @ VTT

Multiscale materials modeling for metal additive manufacturing

Process-Structure-Properties-Performance analysis of Ti-6Al-4V

selective laser melting:

Process-2-Structure: Phase field modeling of rapid solidification

Structure-2-Properties: Crystal plasticity modeling of engineering

material properties

Properties-2-Performance: Micromechanical modeling of fatigue

Summary & Conclusions

Contents

MULTISCALE MATERIALS

MODELING

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VTT Materials & Manufacturing,

Multiscale Materials Modeling Research Group

Main focus on “mesoscale”

modeling, nano-microstructures &

affiliated phenomena.

VTT ProperTune, in-house

multiscale modeling toolset (2013)

Cleavage fracture research. 1st “real”

multiscale modeling work, circa 1997.

“Merger” with tribology, 2001.

As new area

composites, 2008.

Crystal plasticity analysis of high

strength steel: EBSD map (left),

slip (right)



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Multiscale materials modeling: 1) Structure –

Property Correlations

Computational representation of material microstructure: multiphase composite elements, binders, interfaces, porosity & defects of various kinds, ….

Microstructural analysis of resulting material properties: compressive strength, true stress-strain, viscoplastic strain/strain rate, ….

PROPERTY STRUCTURE

Link material microstructure to material properties

CASES: Compression strength of WC-Co, TiC-Ni & hard material composite & metallic microstructures

TiC-Ni

TiC-Ni

MMC

MMC

WC-Co WC-Co

martensitic

WC-Co

WC-Co

MMC

MMC



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Multiscale materials modeling: 2) Structure –

Property – Performance Correlations

Computational representation of material microstructure: metals, composites, texture, multiphase….

Microstructural analysis of resulting material performance, example: short fatigue crack initiation

PROPERTY

STRUCTURE

Link material microstructure and properties to material performance

Microstructural analysis of resulting material properties: strength, true stress-strain, viscoplastic strain rate….

Microstructure founded analysis of individual defects in material microstructure

PERFORMANCE CASE: Microstructure based fatigue analysis of PH steel for metal additive manufacturing



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Multiscale materials modeling: 3) Process –

Structure – Property – Performance Correlations

a) b)

c) d)

e) f)

g) h) g) h) Link material manufacturing process, thermomechanical history, operational conditions etc. to material structure, permeate to properties & performance

Thermomechanical manufacturing process, operational history etc.

PROCESS

PROCESS

STRUCTURE PROPERTY, PERFORMANCE

Solidification, precipitation, grain growth, …

CASE: Material and microstructure design for rapid solidification processes (especially additive manufacturing, thermal spray)



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Incorporates and integrates a range of multiscale

modeling methods and techniques for materials

related problems:

The main application areas of VTT ProperTune are

1) modeling of nano-microstructures and their

properties at mesoscale:

is a collection of software libraries,

interfaces and modeling packages & tools

enables the rapid development &

deployment of modeling solutions

is not a single software package, but rather

a material modeling toolset

…and 2) performance dominating mechanisms and

processes related to component operating

environments or manufacturing (or both):

VTT ProperTune™ is a computational modeling

assisted material design, tailoring and performance

evaluation methodology and software platform.



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Multiscale materials modeling example:

Deformation of Metallic Materials

Dislocation core

phenomena

Dislocation line

behavior

Single crystal

slip behavior

Polycrystalline

microstructure

deformation

Material

properties, e.g.

strength or

ductility

Material

performances,

e.g. fatigue

resistance

structural

damage, aging



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MULTISCALE MATERIALS MODELING AND

INTEGRATED COMPUTATIONAL MATERIALS

ENGINEERING FOR METAL ADDITIVE

MANUFACTURING

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PRODUCT PERFORMANCE

AND COST

Multiscale modeling for

metal additive manufacturing

Discrete modeling of

powder bed physics

→ Powder bed

thermomechanics, laser

matter interaction

Thermodynamics and

phase fields

→ Solidification

microstructure, surface

phenomena & reactive wetting

Modeling material structure → properties and performance

→ Material structure to

material properties causality

→ Material

performance

Topology optimization

→ Optimized

geometric design

Thermomechanical modeling of

selective laser melting

→ Part specific process design,

residual stress & distortion

minization

SLM process design and optimization

Powder and alloy design

Material property & performance design

Part geometry design

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Modeling for metal additive

manufacturing: Concept

Digital material, digital manufacturing and digital product design for metal additive manufacturing. Enable

complex and coupled (e.g. two-way) optimization workflows.

Adopting ICME

principles

Motivation: to properly design for metal AM, an approach incorporating aspects of material, process and

product modeling and design is required.



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Process-Structure-Properties-Performance

Design Concept in Application of ICME



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PROCESS-2-STRUCTURE: PHASE FIELD

MODELING OF RAPID SOLIDIFICATION

MICROSTRUCTURES

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SLM transient thermal

process model, cubic test

samples



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Epitaxial microstructure (*)

(*): figure

from http://iq-

evolution.com

Mechanical

anisotropy

e.g. prone to

cracking and

non-optimal

strength

properties

β grains

Epitaxial growth of columnar grains

Selective laser melting of Ti-6Al-4V and PF

modeling

Two approaches available

for solving:

• Solver 1: dilute binary

model with multi-order

parameter for

orientations

• Solver 2: grand

canonical formulation

with arbitrary free

energies

The former best suited for

N-order parameter

formulation of high rate

phenomena, the latter e.g.

for coarse graining to

greater timescales

(variational formulation of

the solidification problem).



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Selective laser melting of Ti-6Al-4V and PF

modeling

Epitaxial microstructure

Epitaxial growth of columnar grains



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Inoculated equiaxed growth vs columnar growth

Design of inoculated

metallurgies

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Enables the linking of irreversible non-equilibrium thermodynamics studying metastable structures

to imaging based finite elements

Co-simulation approach between phase field

and finite element modeling of

nano/micro/mesostructures



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STRUCTURE-2-PROPERTIES:

CRYSTAL PLASTICITY MODELING OF

ENGINEERING MATERIAL PROPERTIES



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Structure-Property: Metallic microstructures

Introduction of

secondary features

such as laths, twins

etc. to a primary

structure

Using 3D image processing in manipulating nano- and microstructures, to obtain representable 3D images of structure.

Emphasis in metallic and composite (or plainly multi-phase) structures, but no morphological limitations with respect to

the methods themselves.

Introduction of 2nd

phase structures

(precipitates, carbides

etc) to a primary

structure

Tesselation of synthetic

microstructures

Generation of

microstructures

with texture and

grain flow

generation of BCC

structures (~bainite like)

generation of BCC

structures (~martensite

like)

generation of

steel+composite

microstructures



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Structure-Property: Crystal plasticity

Electron backscatter diffraction (EBSD)

image of a high-strength steel,

martensite like basic microstructure

Example: roughly a

single prior austenite

grain

Imaging based

numerical

model of the

grain region

Finite element

mesh of the

grain region

Single crystal

region with

misorientation



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Structure-Property: Crystal plasticity of martensite like

microstructures

Real microstructure discretized to a

computational FE mesh

Subfeatures in martensitic microstructures

Macroscopic stress-strain behavior

Martensitic structures can include:

• Fine microstructure (e.g., prior

austenite size 20-200 um)

• Subfeatures introduce scale

dependency to the material

• Misorientation exist between grains

and subfeatures (especially

packet/block boundaries)

Slip rate and local hardening:

Crystal plasticity approach: deformation

takes place by shear produced by

dislocations



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Structure-Property: Crystal plasticity

Columnar model 1: phase distribution and

grain orientations from phase field model Equiaxed model 1: phase distribution and

grain orientations from phase field model

Columnar model 2:

model 1 + add a

lamellar structure

Equiaxed model 2:

model 1 + add a

lamellar structure



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Structure-Property: Crystal plasticity,

tensile testing Columnar model 1,

direction 1

Columnar model 1,

direction 2 Columnar model,

lamellar substructure

Equiaxed model, lamellar substructure Equiaxed model

• Columnar models are of low strength

and anisotropic response of the

microstructure is clearly visible.

• Equiaxed structure is an

improvement, although the

microstructure is a bit coarse which

shows.

• Lamellar/lath/multiphase structures

are superior in terms of strength.



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Structure-Property: Crystal

plasticity, tensile testing

Columnar

model 1,

direction 1

Columnar

model 1,

direction 2

Columnar

model,

lamellar

substructure

Equiaxed model,

lamellar substructure

Equiaxed

model

Equiaxed

model, lamellar

substructure

Columnar model,

lamellar

substructure

Equiaxed

model

Columnar

model 1,

direction 1

CUMULATIVE PLASTIC SLIP

EQUIVALENT STRESS CONTOURS



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PROPERTIES-2-PERFORMANCE:

MICROMECHANICAL MODELING OF FATIGUE



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Structure-Property-Performance :

Microstructure informed modeling of fatigue

Plastic slip at the free surface of a microstructural domain (high

strength steel) during fatigue cycling. Plastic slip as the failure

criterion.

Deformed model geometry

Region of interest

with respect to

plastic slip and

crack initiation

Larger size packet

feature in microstructure

Slip systems in larger

spot activate ~ “soft

spot”

Surface “waviness” due to finite strain

crystal plasticity

Slip bands &

intrusions for

FC initiation

Plastic strain contours

during tensile loading of a

microstructure.

Crystal plasticity modeling of surface deformation of martensite microstructure (microstructural model generated on the

basis of HR-SEM imaging)



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Structure-Property-Performance : Microstructure

informed modeling of fatigue

1000 cycles, ampl = 2e-3

Ampl = ~50% of yield strength

Cyclic loading to 1000 cycles

• Small amplitudes also cause

significant plasticity in the fine

lath martensite

• Many plausible fatigue sites

• Fatigue evolution laws must be

evaluated locally to upscale to

macroscopic fatigue life

Interframe cycle rate 50

Strain localization

proceeds over

subfeatures e.g.,

prior austenite

grains and packet

boundaries;

however the

relative resistance

of each may be

evaluated

Cumulative plastic slip



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Structure-Property-Performance : Microstructure

informed modeling of fatigue

Microstructure

scale initial crack,

growth about one

grain size via

cumulative slip

based criterion

Introduce a microstructure scale pore, initial location

selected based on local large misorientation

Strain amplitude 5e-4 Strain amplitude 1e-3 Strain amplitude 5e-3 Strain amplitude 1e-2

Analysis of fatigue in microstructures with pre-existing

defects:

Cumulative plastic slip

Cumulative

plastic slip

Cumulative

plastic slip

1st principal

stress

1st principal

stress



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Structure-Property-Performance :

Microstructure informed modeling of fatigue

“Best” microstructure “as good as the

others” for large amplitudes

Despite very small

increments of slip, no

threshold predicted

Columnar,

coarse

lamellar

defects

Introduction of a short fatigue crack size

sharp defect influences cycles to initiation

by a factor of approx. 5

Effect of pore

approx. 2.5

~100 cycles in

strain control



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SUMMARY & CONCLUSIONS



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Summary

Integrated Computational Materials Engineering presently offers

the best overall concept for making materials and the

manufacturing processes part of the digital realm of metal

additive manufacturing. Digitalization of everything materials and

manufacturing processes related feeds ICME.

The methodologies have in many cases yielded case studies

with results significantly improved over those using legacy

approaches enabling the expansion of the AM design space,

new freedoms and features to optimize, tailor and select better

solutions.

The drivers are ultimately better products with optimized material

solutions to market faster with decreased cost. Metal AM needs

an all-around approach merging material, process, CAx and

optimization toolsets and practices.

Thank You!

http://www.vttresearch.com/propertune [email protected]

Acknowledging contributions by:

N. Ofori-Okopu, Northwestern University, USA

N. Provatas, McGill University, Canada

D. Pal, B. Stucker, UofL & 3DSIM, USA

http://www.vttresearch.com/propertune

mailto:[email protected]

multiscale materials modeling for metal additive … of the future/3d... · a material modeling...

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