nonlinear multi-scale modeling of reinforced plastic parts ... · digimat to radioss improves...

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Nonlinear Multi-Scale Modeling of Reinforced Plastic Parts with

DIGIMAT to RADIOSS.e-Xstream engineering

Th. Malo, R. Ramaya, L. Adam, Th. Villette, R. Assaker

[email protected]+32 495 52 56 52

OutlineOutline

Introduction

e-Xstream engineering

Motivation

Digimat to RADIOSS: Nonlinear Multi-Scale Modeling

1. Predict Fiber Orientation

2. Map fiber orientation from Injection Molding Mesh to Radioss Mesh

3. Setup the DIGIMAT material Model

4. Run the Digimat to RADIOSS Analyses

5. Post Process the (Accurate) Results!

ConclusionsTuesday, November 10, 2009 Copyright© e-Xstream engineering, 2009 2

IntroductionIntroduction

The use of composites like reinforced plastics continues to increase in Automotive, Aerospace, ...One of the main drivers for using composites is:ü High stiffness/weight ratio Lighter Greener

The two main barriers to using composites are:1. Technical: Relative low “familiarity” with the material and

suboptimal design & simulation tools2. Economical: Is the composite part cheaper that its metallic

equivalent ?

Predictive Simulation Tools can make the difference

e-Xstream’s Value Proposition

ee--Xstream engineeringXstream engineering

e-Xstreamü Founded in 2003ü Simulation Software & Servicesü 100% focused on material modeling

DIGIMAT Software Platform

Tuesday, November 10, 2009 Copyright© e-Xstream engineering, 2009 4

Target Materials & IndustriesTarget Materials & IndustriesTarget (Mutli-Phase) Materials :

ü Reinforced Plasticsü Rubber: Carbon or Silica Filledü Woven & Non-Woven Composites (CFRP,…)ü Nano-Composites: Nano Clays, Carbon Nano Tubes,…ü Hard Metals: CoWCü Carbonü …

Target Industriesü Material Suppliers: Plastics, Rubber, Carbon,…

ü Automotive: OEMs & Suppliers, Tires, …

ü Aerospace: Airplanes composite structures, Satelites, Launchers,…

ü Electronic & Electric Products: Mobile phones, Electric connectors,…

ü Industrial Goods: Cutting tools, furnaces, Generators, Transformes,…

ü Sports & Leisure, …

Objective: To predict the local & global behavior of a reinforced plastic part subject to a “3-Point Bending Impact”

Material: PAGF30PA630% short glass fibers

6

MotivationMotivation

11/10/2009 Copyright© e-Xstream engineering, 2003-2009

Courtesy of Rhodia

Vz= 5m/s

Local, Anisotropic, Nonlinear, StrainLocal, Anisotropic, Nonlinear, Strain--Rate Rate Dependent Material BehaviorDependent Material Behavior


RADIOSS FEA of Reinforced Plastic PartsRADIOSS FEA of Reinforced Plastic Parts

Geometric nonlinearities (Large Deformations)ContactImplicit/Explicit integrationOptimal mesh refinementOptimal element choiceü 1st/2nd order ü Tet or Hex, Triangle or Quad

Material Reinforced Plasticü Anisotropicü Heterogeneousü Nonlinearü Rate-dependentü Damageü Fatigueü Failureü Etc.


Which Material Model ?

AMODEL AS-4133 - stress-strain curves at 23°C dumbell specimen and test samples from mold II

0

20

40

60

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240

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0strain (%)

stre

ss (M

Pa)

dumbell

Mold II - along the flow

Mold II - across the flow

AMODEL AS-4133 - stress-strain curves at 23°C dumbell specimen and test samples from mold II

0

20

40

60

80

100

120

140

160

180

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220

240

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0strain (%)

stre

ss (M

Pa)

dumbell

Mold II - along the flow

Mold II - across the flow

020406080

100120140160180200220240260280300320

0,0% 0,5% 1,0% 1,5% 2,0% 2,5% 3,0% 3,5% 4,0% 4,5% 5,0% 5,5% 6,0% 6,5% 7,0% 7,5% 8,0Strain

Stre

ss (N

/mm

²)

Damage, 0°, StaticDamage, 0°, 1 s-1Damage, 0°, 100 s-1Damage, 45°, StaticDamage, 45°, 1 s-1Damage, 45°, 100 s-1

TECHNYL C218 V35 Black, 23°C, Eh0

020406080

100120140160180200220240260280300320

0,0% 0,5% 1,0% 1,5% 2,0% 2,5% 3,0% 3,5% 4,0% 4,5% 5,0% 5,5% 6,0% 6,5% 7,0% 7,5% 8,0%Strain

Stre

ss (N

/mm

²)

Damage, 0°, StaticDamage, 0°, 1 s-1Damage, 0°, 100 s-1Damage, 45°, StaticDamage, 45°, 1 s-1Damage, 45°, 100 s-1

TECHNYL C218 V35 Black, 23°C, Eh0

Nonlinear MultiNonlinear Multi--Scale Modeling ProcessScale Modeling Process


Fiber Length Distribution

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10

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90

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25 75 125

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325

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425

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525

575

625

675

725

775

825

875

925

975

1025

1075

1125

Length [µm]

Num

ber

Phase Material & Composite Microstructure-Fiber Shape

-Fiber Weight Fraction

-Fiber Length Distribution

Fiber Orientations

Material DesignProcess Design

RADIOSS

Structure Design

Digimat to Raidoss: Digimat to Raidoss: Nonlinear, Fully Coupled MultiNonlinear, Fully Coupled Multi--Scale ModelingScale Modeling


Nodal coordinates, …

Strain increments,material state, …

Element level

Material level

Stresses and material stiffness

Internal forces and element stiffness

ε

σ

Classical FE process Digimat to Radioss

« In code » model

Nodal coordinates, …

Strain increments,material state, …

Element level

Stresses and material stiffness

Internal forces and element stiffness

Material level

FE model levelFE model level

MF & FEMF & FE--based Micromechanicsbased Micromechanics

Pros

Fast model preparation/solution

Accurate predictions

Enables fully coupled nonlinear multi-scale Analyses

Cons

Ellipsoidal inclusions

Uniformly distributed inclusions

Average per phase (micro) results

Pros

Accurate predictions at the micro scale

Complex inclusion shapes (non ellipsoidal)

Explicit modeling of clustering & percolation

Cons

Relatively Complex RVE generation

Large RVE models (CPU intensive FEA)

Uncoupled multi-scale analyses

Requires mesh optimization

E Σ

Local phase behavior

Global behavior

Localization Averaging

εr σr

EHx rrr Δ=Δ=Δ :)(εε

rrr c εσ Δ=Δ :

εσ Δ=Δ :)( rcc

Tuesday, November 10, 2009 11Copyright© e-Xstream engineering, 2009

MultiMulti--Scale Modeling Analysis Work FlowScale Modeling Analysis Work Flow


Matrix PropertiesReinforcement PropertiesComposite Morphology

Fiber Length/diameterFiber Weight/Volume Fraction

Composite Properties

RadiossMesh

Fiber Orientation

InjectionMesh

InjectionMat Prop.

InjectionProcess Param.

Fiber

OrientationResidualStresses

ResidualTemperature

Micro/macro FEA results

MoldflowMoldex3DSigmasoft

REM3D3DTimon

RADIOSS

1

2

3

4

5

Injection Molding Simulation: Fiber Injection Molding Simulation: Fiber OrientationOrientation


Mold Filling

Fiber Orientation

Injection Molding & Structural FEA MeshInjection Molding & Structural FEA Mesh


Moldflow Mesh6, 438 Triangles20 Layers

RADIOSS Mesh4, 697 Quads10 Layers

Mapping of Fiber OrientationMapping of Fiber Orientation


Map

Mapping of Fiber Orientation: Quality CheckMapping of Fiber Orientation: Quality Check


Skin (Layer 2) Core (Layer 6)

Material DataMaterial Data

The use of DIGIMAT requires:Material data

for each phase of the composite

Micro-structure dataConstituentsMorphology

Two Methods to get these dataü Direct Approach From Measured Polymer Matrix Behaviorü Reverse Approach From Measured Composite Behavior

Copyright e-Xstream engineering 2009

Micormechanics Micormechanics –– DirectDirect ApproachApproachInputü Microstructure Constituents for the Reinforced Material (e.g. PAGF30)

• Matrix Phase (e.g. PA)• Reinforcement Phase(s) (e.g. GF)

ü Material behavior of each Phase:• PA: Elasto-Plastic (E, ν, σy, …)• GF: Elastic (E, ν)

ü Reinforced Material Morphology• Fiber Content (e.g. 30%)• Fiber Orientation (e.g. Orientation Tensor for each element)• Fiber Length (e.g. AR=L/D~25)

Output ü Stress-Strain Response of the Reinforced Material (PAGF30)(for each orientation/element)

Prosü Fully Predictive

Consü Availability of accurate phase dataü Hypotheses of the Mean Field Method


Micormechanics Micormechanics –– ReverseReverse ApproachApproachInputü Microstructure Constituents for the Reinforced Material (e.g. PAGF30)

• Matrix Phase (e.g. PA)• Reinforcement Phase(s) (e.g. GF)

ü Material behavior:• Stress-Strain Curve(s) of the Reinforced Material (e.g. PAGF30)• GF: Elastic (E, ν)

ü Reinforced Material Morphology• Fiber Content (e.g. 30%)• Fiber Orientation (e.g. Aij=(0.8,0.2, 0,..)• Fiber Length (e.g. AR=L/D~20)

Output • Material behavior of Matrix Phase (e.g. PA as Elasto-Plastic (E, ν, σy, …))

Prosü Find missing material dataü Compensates for numerical hypotheses

Consü Depends on the numerical algorithms


Reverse engineering has been done using 2 dumbbells:

ü 1 aligned with the flow directionü 1 transverse to the flow

Multilayer Micro-Structure :ü Describe skin/core effects through the

thicknessü Better describes the composite when

reverse-engineering the material model

DigimatDigimat--MF : MF : Building the material lawBuilding the material law

Courtesy of Rhodia

2011/10/2009 Copyright© e-Xstream engineering SA, 2003-2009

90° 45°

0°

Injection plate

Flow direction

DigimatDigimat--MF : MF : Building the material lawBuilding the material law

2 phases PA+GF compositeü Fibres: Elasticü PA Matrix: ElastoViscoplastic

• Hardening model: Exponential + Linear• Creep model: Prandtl

2111/10/2009 Copyright© e-Xstream engineering SA, 2003-2009

Reverse Engineering of PA fromReverse Engineering of PA from PAGF30 PAGF30

Copyright© e-Xstream engineering, 2009Tuesday, November 10, 2009 22

Matrix phase: PA

Behavior: J2-plasticityexponential + linear hardeningDensity = 1.14 E-06 kg/mm3

Young modulus = 3400 MpaPoisson coefficient = 0.4Yield stress = 35 MPaHardening modulus= 21 MPaHardening exponent= 140Hardening modulus2= 50 MPa

Isotropic method = Spectral

Creep model = PrandtlCreep coefficient = 30 MPaHardening exponent= 3Creep coefficient2= 15 MPa

Inclusion phase: Glass FibersBehavior: Elastic

Density = 2.54 E-06 kg/mm3

Poisson coefficient = 0.22Young modulus = 72000 MPaAR = 23.5

Failure ModelFailure Model

Failure model applied at 3 scalesü Micro (or Phase) Scale PA matrix and/or Fiber Reinforcementü “Pseudo-Grain” Scale “UD” PAGFü Macro (or Composite) Scale PAGF

Failure Modelsü Max stressü Max strainü Tsai-Hillü …

Failure Modelü FPGF

• E11 max = 0.028• E22 max = 0.052


Isotropic Isotropic Johnson Cooke Model Isotropic Isotropic Johnson Cooke Model


E 10000 MPav 0.37a 100 MPab 500 MPan 0.4

eps max 0.025

Digimat to Radioss: Digimat to Radioss: Local/ Anisotropic/StrainLocal/ Anisotropic/Strain--Rate/Pseudo Grain FailureRate/Pseudo Grain Failure


ConclusionsConclusions

Nonlinear Mean Field homogenization techniques enable an accurate prediction of the global (macroscopic) response of reinforced plastics based on:

ü The behavior of each phase: polymer & reinforcementsü The microstructure defined by the

• Fiber content: 30%, 40%...• Fiber length: short/long/distribution of length• Fiber orientation: measured (e.g. Micro Tomography) or Precited (e.g. Injection

Molding) Locally

The material response of the (in-situ) polymer matrix is not always available. Reverse Engineering is an attractive method to:

ü Generate Missing Dataü Compensate for some numerical approximations

Digimat to RADIOSS improves considerably the accuracy of the FEAof Reinforced Plastic Parts thanks to an accurate modeling of the local nonlinear anisotropic and strain-rate dependent response of the fiber reinforced plastic material.


nonlinear multi-scale modeling of reinforced plastic parts ... · digimat to radioss improves...

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