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Testing for Crash & Safety Simulation

Hubert Lobo

DatapointLabsNew York, USA

CAHRS Workshop

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DatapointLabs

Research quality material testing

ISO 17025 production environment

Results in 5 days (48 hour RUSH service)

Web-based quotation & data delivery

Domain expertise in CAE material calibration

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expert material testing

TestPaks® = Materials testing + CAE material parameter conversion

metal, plastic, foam, rubber, composites…

over 20 CAE software codes

testing

Your CAE

data conversionmaterials +

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Topics

A test philosophy for representing rate dependency of materials Experimental technique including sampling and specimen geometries Assessment of crash material data quality, expected trends & validation Specific comments for unfilled and fiber-filled polymers, foams, rubber and metals.

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Getting pertinent properties

Importance of measuring the right property

Artifact free dataProperly designed experiments

eg. not using crosshead displacementto calculate strain

Traceable data (ISO 17025)NIST traceable instruments

Certified trained technicians

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Getting the right samples

Spatial variationProperties vary with location

Forming, stretching, molding…

Environmental variationAgeing and conditioning

Process variationDegradation from processing

Recycled materials

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Metals

Relatively well behaved

Models designed to match behavior

Challenges lie with post yield non-Mises failure envelopes

Scaling of yield surface with strain rate

Work of Nakajima, Dubois, Hooputra

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Plastics

Not well behaved

Models not designed for plastics crash simulation

Complex models are expensive

Can we develop best practices for adapting common models to plastics

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Plastics Behavior - Basics

Non-linear elasticity

Elastic limit well below classical yield point

Significant plastic strains prior to yield

Post-yield with necking behavior

0

5

10

15

20

25

30

35

0.0 5.0 10.0 15.0 20.0

Engineering Strain (%)

Engin

eerin

g St

ress

(MPa

)

data

Plastic Point

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Plastics Rate Effects

Modulus may depend on rate

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Plastics Rate Effects

Fail strain may be rate dependent

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Material Testing

Instron servo-hydraulic UTM

Dynamic load cell

Test at 0.01, 0.1, 1. 10, 100/s strain rates

Temperatures: -40 to 150C

tens_slow.mpg

Tens.mpg

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Test Specimens

ASTM D638Type V

PreparationCNC from plaque

CNC from part

Molded

Variabilityprocessing

orientation

thickness

gate region

E1

E2

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Modeling simple ductile plastics

Modulus is not rate dependent

Large strains to failure

Post-yield necking

Plasticity curves vary with strain rate

Failure strain independent of strain rate

LS-DYNA, ANSYS, ABAQUS, PAMCRASH

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Choosing EMOD

0

5

10

15

20

25

30

35

0.0 5.0 10.0 15.0 20.0

Engineering Strain (%)

En

gin

ee

rin

g S

tre

ss (

MP

a)

data

Plastic Point

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Post-yield with necking (Deihl)

0

10

20

30

40

50

60

70

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Strain mm/mm

Str

ess

MP

a

UTM1-39.62-1

UTM1-39.62-2

yield point

necking starts

neck propagation

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Fail Limitations

When FAIL f(strain rate)

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0

5

10

15

20

25

30

35

40

1.E-02 1.E-01 1.E+00 1.E+01 1.E+02

Strain Rate(/s)

Ten

sile

Str

engt

h (M

Pa)

data

Cowper Symonds

Eyring

Modeling Rate Dependency

Cowper SymondsDoes not correlate well with plastics rate dependency

LCSRCapture model independent behavior

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Eyring Model

Eyring ModelYield stress v. log strain rate is linear

Best form for plastics

Fit yield stress v. log strain rate data to Eyring equation

Can submit to LSDYNA MAT24 as table using LCSR

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MAT24 validation

0

10

20

30

40

50

60

0 0.05 0.1 0.15 0.2 0.25 0.3

Strain (mm/mm)

Str

ess

(MP

a)

LS-DYNA Simulation

Tensile Experiment

MAT 24 Model

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Brittle plastics

Modulus is rate dependent

Small strains to failure

Brittle failure

Failure strain decreases with increasing strain rate

LSDYNA MAT19

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Methodology for MAT 19

Determine elastic limit at quasi-static strain rate

Use elastic limit for von-Mises yield

Define failurefailure stress v. strain rate table

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Ductile-brittle transitions

Non-linear behavior

Failure depends on strain rate

ModelsLS-DYNA MAT89

PAMCRASH 103

Abaqus *ELASTIC *PLASTIC,Rate

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Fiber Filled Plastics

Digimat MXMaterial model reverse engineered from standard experiment

Perform injection-molding simulation

Apply Digimat material model to transfer data to crash simulation

Crash model has spatially oriented properties

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Basic Digimat TestPak Protocol

Mold 100X300X3.16mm plaquesEdge gated on 100 mm end

Long flow length

Fully developed flow

Highly fiber orientation

Cut test specimens by CNC

5 specimens each (0°, 90° )

Obtain true stress-strain data

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Advanced Models

MATSAMP (LS-DYNA)

Standard rate dependent model

Add non-mises failure envelopeCompression

Shear

Add triaxialityPost yield transverse strain

Add unloading

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Pros and Cons

Better failure envelope modeling

Greater cost

More complex model

Greater simulation accuracy in difficult cases

Cost-benefit not certain for general use

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Foams

Different deformation modesCrushable

Elastic with or without damage

Visco-elastic

Large volumetric strain component

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Effect of Poisson’s Ratio = 0

Material compacts by eliminating airNo lateral deformationPoisson’s Ratio -> 0Axial strain volumetric strainTrue for

open cell foamscrushable foams

May not be true forclosed cell foamselastomeric foams

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Typical Stress-Strain Data

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.050

0 20 40 60 80 100

Engineering Strain (%)

En

gin

ee

rin

g S

tre

ss (

MP

a)

Zone 1 Zone 2 Zone 3

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Test Strategy

Compressive stress-strain5 decades of strain rate

.01, .1, 1, 10, 100 /s

Temperatures -100 to 150C

Optional testsTensile (for cut-off stress)

Shear (as required)

Hisp_comp.mpg

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Test Instruments

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PU Foam-stress strain

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Strain (mm/mm)

Stre

ss (M

Pa)

0.01/s fit

0.1/s fit

1/s fit

10/s fit

100/s fit

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PU Foam- rate effects

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PU Foam recovery

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0 20 40 60 80 100

Engineering Strain (%)

En

gin

ee

rin

g S

tre

ss (

MP

a)

Load

Unload

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Conclusions

Choice of material model depends onmaterial

test data

situation complexity

Proper selection = reasonable model

Simple improvements can add power

Validated models represent baseline

Models can be tuned for multi-axial loadings

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