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LS-DYNA Automotive Material Failure Calibration

30 Chapters

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Course overview

scope, objectives, and the role of material failure calibration in automotive crashworthiness simulation.

objectivesmaterial

LS-DYNA material failure modeling landscape

available failure criteria, damage models, and their applicability to automotive materials.

LS-DYNAmaterial

Automotive materials under crash loading

steel, aluminum, magnesium, composites, and plastics—failure mechanisms and calibration challenges.

Automotivematerials

Experimental characterization for failure calibration

tensile, shear, bulge, and fracture tests; specimen design and data acquisition.

Experimentalcharacterization

Calibration workflow overview

from raw test data to validated LS-DYNA material cards, including iterative parameter identification.

Calibrationworkflow

MAT_024 (Piecewise Linear Plasticity) with failure

strain-based criteria, element deletion, and calibration for mild steels.

MAT_123 (Modified Piecewise Linear Plasticity) and its failure options

calibration for high-strength steels and aluminum alloys.

GISSMO damage model

formulation, parameters, and calibration strategy for ductile metals.

GISSMOformulation

Calibration of GISSMO using tensile and shear tests

extracting instability and fracture strains, regularization, and mesh size dependency.

CalibrationGISSMO

DIEM damage model

comparison with GISSMO, calibration steps, and application to automotive alloys.

Johnson-Cook failure model

parameter identification from split Hopkinson pressure bar and quasi-static tests.

Johnson-Cookparameter

Calibration of strain-rate-dependent failure

using MAT_024, MAT_123, and rate-sensitive damage models.

Calibrationstrain-rate-dependent

Triaxiality and Lode angle effects

calibrating failure loci for aluminum extrusions and castings.

Triaxialitycalibrating

Spot weld and joint failure calibration

using MAT_100, MAT_240, and cohesive zone models in LS-DYNA.

Calibration of adhesive and composite failure

MAT_054, MAT_058, and MAT_261 for automotive structures.

Calibrationadhesive

Mesh size regularization in failure calibration

characteristic length, damage evolution, and non-local approaches.

regularizationcalibration

Element formulation and failure

shell vs. solid elements, hourglass control, and their impact on calibration accuracy.

formulationelements

Calibration for forming and manufacturing effects

pre-strain, residual stress, and their influence on crash failure.

Calibrationmanufacturing

Inverse calibration using LS-OPT

parameter identification, objective functions, and surrogate-based optimization.

calibrationLS-OPT

Validation of calibrated material models

component-level tests, full-vehicle simulations, and correlation metrics.

Validationcalibrated

calibration of a DP780 steel for frontal crash simulation—from coupon tests to full vehicle model.

calibrationDP780

calibration of an aluminum alloy for side impact and battery enclosure intrusion.

calibrationaluminum

calibration of a glass-fiber reinforced thermoplastic for pedestrian protection and interior trim.

calibrationglass-fiber

Calibration of failure for high-strength die-cast aluminum

porosity, strain rate, and temperature effects.

Calibrationhigh-strength

Calibration of failure in laser-welded blanks and tailor-welded blanks

weld line properties and failure.

Calibrationlaser-welded

Calibration of failure for magnesium alloys

challenges in ductility, twinning, and rate sensitivity.

Calibrationmagnesium

Calibration of failure for carbon-fiber composites

MAT_054, MAT_058, and MAT_261 with progressive damage.

Calibrationcarbon-fiber

Calibration of failure for polymers and elastomers

MAT_089, MAT_181, and MAT_187 for automotive applications.

Calibrationpolymers

Advanced topics

machine learning-assisted calibration, Bayesian parameter estimation, and uncertainty quantification.

Advancedlearning-assisted

Best practices, common pitfalls, and documentation

ensuring traceability, reproducibility, and model quality in LS-DYNA failure calibration.

practicespitfalls