Material Insights by CAE Type

LS-DYNA

Software for Creating and Managing Material Specifications 

Material specifications define properties for incoming materials to meet required criteria. We present software that manages creation of material specifications, input of properties and material composition; and provides a way to evaluate qualification per specification. While it is designed for OEM/Tier n environments, it is also applicable for materials suppliers.

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Comments on the Testing and Management of Plastics Material Data 

Plastics appeared as design materials of choice about 30 years ago. They brought with them huge design challenges because their multi-variable, non-linear nature was not well understood by engineers trained to work in a linear elastic world. We outline a 20 year journey accompanying our customers in their efforts to understand and simulate these remarkable materials to produce the highly reliable plastic products of today. We discuss challenges related to processes such as injection molding vs. blow-molding; coping with filled plastics; the difficulties of modeling polymers for crash applications. We include our latest findings related to volumetric yield in polymers and its relationship to failure. We describe the material database technology that was created to store this kind of multi-variable data and the analytical tools created to help the CAE engineer understand and use plastics material data.

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Applying Digital Image Correlation Methods to SAMP-1 Characterization 

SAMP-1 is a complex material model designed to capture non-Mises yield and localization behavior in plastics. To perform well, it is highly dependent on accurate post-yield material data. A number of assumptions and approximations are currently used to translate measured stress-strain data into the material parameters related to these inputs. In this paper, we look at the use of direct localized strain measurements using digital image correlation (DIC) as a way to more directly extract the required data needed for SAMP-1.

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Pre-processor Software for Calibration of LS-DYNA® Material Models

LS-DYNA contains a wealth of material models that allow for the simulation of transient phenomena. These models are often quite complex and difficult to calibrate. We present CAE Modeler, a generalized pre-processor software used to convert material property data into material parameters for different material models used in CAE. In this paper, CAE Modeler is used to streamline the conversion of rate dependent stress-strain data into material parameters for the MAT_024 material model. The interactive software is capable of handling all three rate dependency options of MAT_024 and outputs a data file that can be read directly into LS-DYNA. Support for other material models is envisaged.

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Testing for Crash & Safety Simulation

The testing of materials for use in crash and safety simulations and the conversion of test data into material models is a process that is not well standardized in the industry. Consequently, CAE users face uncertainty and risk in this process that can have a negative impact on simulation quality. In this workshop, we present approaches currently used in the US for the gathering of high quality test data plus the acclaimed Matereality CAE Modeler software that is used to transform high strain-rate data into crash material cards.

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

Many material models are available for crash simulation. However, common models are not designed for plastics. We present best practices developed for adapting common models to plastics, as well as best testing protocols to generate clean, accurate rate-dependent data. In addition, we present a streamlined process to convert raw data to LS-DYNA material cards, and harmonized material datasets that allow the same raw data to be used for other crash and rate-dependent analysis software.

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A Robust Methodology to Calibrate Crash Material Models for Polymers

High strain rate material modelling of polymers for use in crash and drop testing has been plagued by a number of problems. These include poor quality and noisy data, material models unsuited to polymer behaviour and unclear material model calibration guidelines. The modelling of polymers is thus a risky proposition with a highly variable success rate. In previous work, we tackled each of the above problems individually. In this paper, we summarize and then proceed to present a material modelling strategy that can be applied for a wide variety of polymers.

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