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1 © 2009 carhs.training gmbh Behavior-based Material Model Selection and Calibration of Plastics for Crash Simulation Hubert Lobo DatapointLabs Automotive CAE Grand Challenge 2010 30th – 31st March, 2010

Automotive CAE Grand Challenge 2010

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Behavior-based Material Model Selection and Calibration of Plastics for Crash Simulation. This presentation covers the testing of plastics for crash applications and the subseqent use of Matereality SAAS software to convert this data into material cards for ANSYS, LSDYNA, Abaqus.

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Page 1: Automotive CAE Grand Challenge 2010

1© 2009 carhs.training gmbh

Behavior-based Material Model Selection and Calibration of Plastics for Crash Simulation

Hubert LoboDatapointLabs

Automotive CAE Grand Challenge 201030th – 31st March, 2010

Page 2: Automotive CAE Grand Challenge 2010

2© 2009 carhs.training gmbh

DatapointLabs: Expert material testing… since 1995

Material properties for product development • Over 1,000 materials tested each year• Wide variety of materials• Over 200 types of physical properties

CAE Material Model Calibration Services• 25 CAE codes supported• Abaqus, ANSYS, LS-Dyna,

NX NASTRAN, Moldflow, Polyflow, in-house

– Plastic

– Rubber

– Film

– Metal

– Foam

– Composite

– Cement

– Ceramic

– Paper

– Wire

– Fiber

ISO 17025 Certified

Page 3: Automotive CAE Grand Challenge 2010

3© 2009 carhs.training gmbh

Problem statement and needs

Many material models are available for crash simulation

Common models are not designed for plastics

Develop best practices for adapting common models to plastics

Develop best testing protocols for clean, accurate rate-dependent data

Develop streamlined process to convert raw data to LS-DYNA cards

Harmonized material datasets to use same raw data for • Abaqus• PAM• RADIOSS..

Page 4: Automotive CAE Grand Challenge 2010

4© 2009 carhs.training gmbh

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 (%)En

ginee

ring S

tress

(MPa

) data

Plastic Point

Page 5: Automotive CAE Grand Challenge 2010

5© 2009 carhs.training gmbh

Plastics Rate Effects

Modulus may depend on rate

Page 6: Automotive CAE Grand Challenge 2010

6© 2009 carhs.training gmbh

Plastics Rate Effects

Fail strain may be rate dependent

Page 7: Automotive CAE Grand Challenge 2010

7© 2009 carhs.training gmbh

Effect of fiber fillers

Higher modulus

Small strain to failure

Brittle failure

No post-yield behavior

Anisotropy

Page 8: Automotive CAE Grand Challenge 2010

8© 2009 carhs.training gmbh

Material Testing

Instron servo-hydraulic UTM

• Dynamic load cell

• -40 to 150C

•Testing Protocol

• ASTM D638

• Tensile Stress strain data

• 5 decades of strain rate

- 0.01/s

- 0.1/s

- 1/s

- 10/s

- 100/s

Page 9: Automotive CAE Grand Challenge 2010

9© 2009 carhs.training gmbh

Test Specimens

ASTM D638Type V

Preparation

• CNC from plaque

• CNC from part

• Molded

Variability

• processing

• orientation

• thickness

gate region

E1

E2

Page 10: Automotive CAE Grand Challenge 2010

10© 2009 carhs.training gmbh

Creating Harmonized Pedigreed Datasets

Matereality datasets comprise

all stress strain curves (each replicate)

all strain rates

all test parameters

data source and traceability

statistical data

Data in full digital form ready for post-processing and export into

LS-Dyna

Abaqus/Explicit

ANSYS Autodyn

Page 11: Automotive CAE Grand Challenge 2010

11© 2009 carhs.training gmbh

Material Dataset loaded to Matereality

Page 12: Automotive CAE Grand Challenge 2010

12© 2009 carhs.training gmbh

MAT 24 – 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

Page 13: Automotive CAE Grand Challenge 2010

13© 2009 carhs.training gmbh

MAT 24 Automated data conversion

Page 14: Automotive CAE Grand Challenge 2010

14© 2009 carhs.training gmbh

Rate Dependency Tuning

Page 15: Automotive CAE Grand Challenge 2010

15© 2009 carhs.training gmbh

Modeling Post-Yield & Failure

Page 16: Automotive CAE Grand Challenge 2010

16© 2009 carhs.training gmbh

Writing the material file

Page 17: Automotive CAE Grand Challenge 2010

17© 2009 carhs.training gmbh

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

Page 18: Automotive CAE Grand Challenge 2010

18© 2009 carhs.training gmbh

MAT 24 – Fail Limitations

When FAIL f(strain rate)

Page 19: Automotive CAE Grand Challenge 2010

19© 2009 carhs.training gmbh

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

en

gth

(M

Pa

)

data

Cow per Symonds

Eyring

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

en

gth

(M

Pa

)

data

Cow per Symonds

Eyring

MAT 24 – Rate Dependency

Cowper Symonds

• Does not correlate well with plastics rate dependency

LCSR

• Capture model independent behavior

Page 20: Automotive CAE Grand Challenge 2010

20© 2009 carhs.training gmbh

MAT 24 – LCSR-Eyring

Eyring Model• Yield stress v. log strain rate is linear• Best form for plastics

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

Submit as table using LCSR

Page 21: Automotive CAE Grand Challenge 2010

21© 2009 carhs.training gmbh

MAT 19 – Brittle plastics

Modulus is rate dependent

Small strains to failure

Brittle failure

Failure strain decreases with increasing strain rate

Page 22: Automotive CAE Grand Challenge 2010

22© 2009 carhs.training gmbh

MAT 19 – Methodology

Determine elastic limit at quasi-static strain rate

Use elastic limit for von-Mises yield

Define failure

• failure stress v. strain rate table

Page 23: Automotive CAE Grand Challenge 2010

23© 2009 carhs.training gmbh

MAT 89 – Ductile-brittle

Non-linear behavior

Failure depends on strain rate

Can handle ductile-brittle transitions

Uses stress-strain curve

Limited to shell elements

Page 24: Automotive CAE Grand Challenge 2010

24© 2009 carhs.training gmbh

MAT 89 – Methodology

Submit stress-strain curve

Submit EMOD

Submit rate dependency via LCSR-Eyring

Submit failure strain v. strain rate via LCFAIL

Page 25: Automotive CAE Grand Challenge 2010

25© 2009 carhs.training gmbh

MAT 89 – Workings

Internally decompose quasi stress-strain curve• Use EMOD for von Mises limit• Rest of the curve is elastic-plastic• Rate dependency via LCSR• Failure via LCFAIL

Page 26: Automotive CAE Grand Challenge 2010

26© 2009 carhs.training gmbh

Conclusions

Choice of material model depends on• material• test data

MAT89 is generically applicable

Proper selection = reasonable model

Simple improvements can add power

Validated models represent baseline

Models can be tuned for multi-axial loadings

Matereality data conversion streamlines material parameter creation

Matereality raw dataset and work flow can be applied to other CAE