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Combining Experiments, PolyUMod,

Kornucopia, and Abaqus to Create

Accurate FE Scratch Simulations

DuPontTed Diehl, Li L in, Ye Zhu, John J. Podhiny, Richard T. Chou, and Jeffrey A. Chambers

Veryst Engineering, LLCJorgen S. Bergstrom, Xiaohu Liu

2013 SIMULIA Community Conference

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2

Overview

Goal of Project

Complexity of Scratch

Material Characterization

Material Testing

Constitut ive Approach, and Calibration

FEA Modeling Approach To Simulate Scratch

Correlating 3D Physical Scratch Data with FEA Simulation Results

Open Issues More To Do!

Conclusions

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Project Goals

Develop Abaqus models to predict scratch performance of polymeric

materials

Predict residual depth and residual shapeof scratch.

Including time dependent partial self-healing behavior of many

polymers.

Material Characterization Include nonlinear viscoplastic nature of polymers via PolyUMod.

Utilize efficient Ziggurat testing protocols and MCalibration for material

calibration.

Develop improved methods to compare 3D physical scratch test data toAbaqus scratch simulation results.

Utilize Kornucopia analysis tools to process and transform large

amounts of messy, 3-D data for correlations.

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Polymer Materials Used in Study

Three polymeric materials were studied.

DuPont Surlyn grades (an ethylene copolymer ionomer).

Surlyn 9950

Surlyn 1706/1707 blend

Materials are differentiated from each other by such factors as their

percent neutralization, acid content and other formulation make-up.

PMMA

A polymethylmethacrylate.

PMMA is noticeably different from the Surlyn materials.

PMMA is stiffer and harder.

PMMA is based on the molecule methyl methacrylate and is not an

ethylene copolymer ionomer.

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Complexities of Polymer Scratch

5

Photographs of 3 different polymers after

being scratched by the same indenter

Indenter load

progressively

increased

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Complexities of Simulating Polymer Scratch

The following are required for viable simulations and scratch validation.

Material experiments that exercise the sample to generate sufficient data to

characterize elastic, inelastic, and recovery behavior, including rate/time

dependence and large strain response.

A polymer constitutive model capable of representing such complex behavior.

Robust FEA methods that can incorporate the advanced material model,

support sliding contact, and can handle extremely large strains which will

cause severe element distortions.

Detailed polymer scratch experiments with 3-D surface imaging technology to

capture the scratched profile for comparison to the FEA simulations.

A method to manipulate and correlate large amounts of data from tests and

models.

Including a method to correlate 3-D scratch surfaces.

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What about Polymer fracture?

This is important, but was notconsidered in th is in itial study.

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Material Characterization

Physical Tests and Constitutive Models

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The ZigguratTest Protocol

An efficient all-in-one material testing protocol with these key benefits:

Exercises elastic, inelastic, loading and unloading behavior.

Adds stress relaxation behavior at several strain levels in same test

Can be applied to compression (shown), tension, shear, equibiaxial

8

Time

Com

pressiveStrain

Compre

ssiveStress

Compressive Strain

Applied Boundary Conditions Materials Response

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Application of ZigguratTest Protocol to

Polymers with Significant Plasticity

The previous slide presentedan idealizedZiggurat protocol.

Elastomer testing often looks quite

similar to picture on right.

Tests of polymers that exhibit

noticeable inelastic (plasticity)behavior often need a modified

ziggurat protocol.

Key goal of Ziggurat protocol

is to get several relaxation

holds on both the loading and unloading curves. Depending on relaxation behavior of material, time holds might be very

long compared to loading ramps of various strain segments.

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Ziggurat Protocol

(Surlyn 1706/1707)

Key items

Asymmetric strain/time BC

Very long time holds

Difficulty with strain control

(cross-head) vs. laser gage

strain measurements.

Laser measures used for

material calibration.

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0 10 20 30 40 50 60 70

0

50

100

150

0 10 20 30 40 50 60 70

0

50

100

150

Comp. engineering strain (%)

Comp.engineeringstress(MPa)

Comp.e

ngineeringstress(MPa)

Comp engineering strain (%)

a) Strain computed from

cross-head displacementb) Strain computed from

laser gages measuring

specimen height

0 10 20 300

10

20

30

40

50

60

Compeng.strain(%

)

Comp.eng.stress

(MPa)

0 10 20 300

25

50

75

100

125

150

Time (minute)

c) Strain and stress data as a function of time

Strain co mputed from laser gages

measuring specimen height

Idealized Protocol

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Ziggurat Protocol

(Surlyn 1706/1707)

Key items (continued)

Raw data (not shown):

35,000 points, non-uniform t.

Strain data had a small amount of noise

due to optical laser gages.

Data had start-up distortions in the initial

small-strain regime due to small geometry

irregularities in the samples.

Kornucopia utilized to clean-up and re-sample

data prior to MCalibration analysis. This improves both accuracy and efficiency of material law calibration

process.

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Ziggurat Protocol

(Surlyn 1706/1707)

Raw data clean-up steps:

Semi-automatic algorithm separates data into

various Ziggurat segments.

Strain holds and all the other segments

Each segment smoothed to remove noise

Distortion at the beginning of the test was

trimmed and corrected with linear extrapolation.

Each segment resampled

Load/unload segments 100 equal time

points

Strain holds 100 logarithmically spaced pts.

Data clean-up significantly improved the data quality and reduced the dataset

from 35,000 points to less than 1,000 points.

Reusable worksheet allowed for efficient, repeatable, and traceable data

cleanup of all Ziggurat tests for all materials.

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PolyUMod Three Network Model (TNM)

Material data exhibits non-linear viscoplastic response with significant flow

and partial recovery after unloading. Utilize PolyUMod library of user-material models for Abaqus

The Three Network Model is a rheological approach with non-linear

springs and dashpots capable of representing materials.

13

See papersreferences for

details of the

governing

equations

PolyUMod and

MCalibration are

software products

from Veryst

Engineering, LLC.

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PolyUMod Three

Network Model (TNM)

Total stress is given by sum of theCauchy stress tensor in each

network.

Stress response of each of the 3

networks

Hyperelastic Arruda-Boyce

eight-chain model.

The stiffness of network B is taken to evolve with the plastic strain

accumulation in Network A.

The rate of viscoplastic flow of Networks A and B is given by a power law

expression of the driving deviatoric shear stress and temperature, and theflow resistance is taken to be pressure dependent.

This material model exhibits true plasticity despite the presence of the

Network C component. The cause of the plasticity is the energy barrier

for flow that is inherent in the flow equations.

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Calibrating TNMwith Test Data via MCalibration

Utilize Compression with Friction load case,

MCalibration automatically creates an Abaqus FE model of theexperimental test setup and boundary conditions (including friction).

Allows model to closely represents the configuration of actual tests.

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Calibrating TNMwith Test Data via MCalibration

MCalibration performs nonlinear search to find material law parameters that

minimize error between model and actual test data. Several controls and options to allow user influence over process.

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TNMRepresentations of Material Test Data17

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TNMRepresentations of Material Test Data18

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Abaqus Simulation of Scratch

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Abaqus/Explicit Model

to Simulate Scratch

Key features & approach

Explicit model selected to more

robustly handle potential severe

deformations.

100 micron radius scratch tip

rigid surface

Polymer specimen was divided

into two regions (tied together)

Coarse region (500 C3D8R),

Fine region (55,000 C3D8R).

Adaptive re-meshing (by solver) used for fine mesh region.

Mass scaling is used to speed-up the simulation.

More to be said about this shortly.

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Abaqus/Explicit Model to Simulate Scratch

The scratch simulations were performed in three steps:

(example for Surlyn 1706/1707 blend simulation)

1. Indenter pushed vertically down into

material 60 m in 0.05 sec.

2. Indenter moved horizontally 0.6 mm

in 0.15 sec.

3. Indenter unloaded by moving vertically

upward 66 m in 0.05 sec.

Allow material to creep recover

(>20 seconds in the FEA model)

Notes:

Different scratch depths used for other materials

Simulations were performed in displacement control

Physical scratch experiments were performed in load control

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Step 1

Step 2

Step 3

GIFMP4

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http://c/Users/Ted/Documents/Presentations%20and%20Papers/other/ABAQUS/2013_conf/_Presentation/ScratchSimulation_Diehl_etal/FEA_scratch_scratch_1706-1707mix.mp4http://c/Users/Ted/Documents/Presentations%20and%20Papers/other/ABAQUS/2013_conf/_Presentation/ScratchSimulation_Diehl_etal/FEA_scratch_scratch_1706-1707mix.mp4

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Abaqus/Explicit Model to Simulate Scratch

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Mass Scaling

Issues with

Explicit Model

Compared to Courant stability ofmodel, scratch time is long,

especially for creep recovery.

Use staged mass scaling to

speed-up simulation.

Caused largeoscillations

Minimized by mass-

proportional Rayleigh

damping.

Segmented filtering by

Kornucopia shows noticeable

discontinuity caused by staged

mass-scaling.

Recent analysis shows we

were just too aggressive!

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0 5 10 15 20 250.06

0.04

0.02

0

0 1 2 3 40.06

0.04

0.02

0

0 1 2 3 4

0.06

0.04

0.02

0

0 5 10 15 20 250.06

0.04

0.02

0

Time (sec)

Displacement(mm)

D

isplacement(mm)

Displacement(mm)

Displacement(mm)

Noticeable

Discontinuity

Stage 2, t=0.3msec

Stage 1, t=0.029msec

Stage 3

t=3.0msec

All stages, No smoothing

Stage 1, smoothed

Stage 2, smoothed

Stage 3, smoothed

Stage 1, smoothed

Stage 2, smoothed

Stage 3, smoothed

Creep recovery of single node

in scratch region

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Physical Scratch Tests and

Correlations to Abaqus Simulations

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How to Compare Experiments and FEA???

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Visual image

Zygo optical scan

Abaqus top

surface

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Typical Physical Scratch Tests

Zygo 3-D optical surface profile (Surlyn 9950, 1.5N Load, ~ 1 day post scratch)

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Many

drop-outs

in data

Limited

3-D

viewing

Limited

data

analysis

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Typical Physical Scratch Tests

Zygo 3-D optical surface profile (Surlyn 9950, 1.5N Load, ~ 1 day post scratch)

27

Improvements

after Data

Healing via

Kornucopia

and Mathcad

0 100 200 300 400 50030

40

50

60

Healed

Raw

Distance (micron)

Z(micron)

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Further Scratch Test Data Analysis

(PMMA ~ 1 day post scratch)

Collapsing

many surface

cross-sectionsinto a single

average

cross-section

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Further Scratch Test Data Analysis

(Surlyn 1706/1707 blend ~ 1 day post scratch)

Collapsing

many surface

cross-sectionsinto a single

average

cross-section

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Similar Post-Process of FEA Scratch Results

(Surlyn 1706/1707 blend ~ 25 seconds post scratch)

Collapsing

many surface

cross-sectionsinto a single

average

cross-section

FEA post-processing

required addit ional

surface remapping

of results to enable

slicing

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Final Cross-Section Correlations

Average scratch cross-sections show that Abaqus/Explicit models using

PolyUMod TNM material model correlates well across several diverse

materials.

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Open Issues

Polymer fracture

Difficult to model as many fracture locations can occur.

Need to assess viable routes for this very complicated.

Creep recovery over long t ime periods

The amount of mass scaling we used was shown to be a bit aggressive.

Lesser mass scaling would be better, but makes even longer run

times.

Switching from Abaqus/Explict back to Abaqus/Standard not possible

because of adaptive meshing approach used.

We only computed for 25 seconds of creep recovery physical tests were

for 1 day!

A DSP concept Frequency Warping.

Nonlinearly warp time-domain implication of visco material constants

so as to compress, in time, the short and long scale meanings of

constants. Similar to filter warping or structural frequency warping.

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Conclusions

Demonstrated that accurate models of Polymeric Scratch are possible.

Combined:

Detailed physical material tests (Ziggurat Protocol)

PolyUMod Three Network (material) Model for Abaqus

MCalibration material calibration

Abaqus/Explicit using mass scaling and adaptive re-meshing Kornucopia data analysis

Methodology developed and demonstrated using three different polymeric

materials, two DuPont Surlyn grades and PMMA.

Demonstrated efficient method to compare complex 3-D scratch results

Open issues

Polymer fracture

Improved methods to simulate long creep recovery times

Something to explore Frequency Warping

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