Material Insights by Material Type

Foams

Software for Creating LS-DYNA Material Model Parameters from Test Data 

LS-DYNA software contains a wealth of material models that allow for the simulation of transient phenomena. The Matereality® CAE Modeler is a generalized pre-processor software used to convert material property data into material parameters for different material models used in CAE. In a continuation of previously presented work, we discuss the extension of the CAE Modeler software to commonly used material models beyond MAT_024. Software enhancements include advanced point picking to perform extrapolations beyond the tested data, as well as the ability to fine-tune the material models while scrutinizing the trends shown in the underlying raw data. Advanced modeling features include the ability to tune the rate dependency as well as the initial response. Additional material models that are quite complex and difficult to calibrate are supported, including those for hyperelastic and viscoelastic behavior. As before, the written material cards are directly readable into the LS-DYNA software, but now they can also be stored and catalogued in a material card library for later reuse.

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Providing an Experimental Basis in Support of FEA 

The use of CAE in design decision-making has created a need for proven simulation accuracy. The two areas where simulation touches the ground are with material data and experimental verification and validation (V&V). Precise, well designed and quantitative experiments are key to ensure that the simulation initiates with correct material behavior. Similar validation experiments are needed to verify simulation and manage the risk associated with this predictive technology.

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Material Parameter Calibration Services for Abaqus Non-Linear Material Models

DatapointLabs' TestPaks (material testing + model calibration + Abaqus input decks) for rate-dependent, hyperelastic, viscoelastic, NVH, and the use of Abaqus CAE Modeler to transform raw data into material cards will be presented. A representative from Idiada will present a case study explaining the use of DatapointLabs’ material data and TestPaks for simulation.

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Understanding and Coping with Material Modeling Limitations in FEA 

The limitations of modeling materials for simulation are discussed, including lack of clarity in material model requirements, gaps between the material data and the model to which it will be fitted, issues in obtaining pertinent properties, difficulties in parameter conversion (fitting), and preparation of input files for the software being used. Means to address these limitations are presented, including understanding the model completely, measuring the correct data with precision on the right material, selecting the best model for the data and ensuring the best fit of the model to the data, validating the model against a simple experiment, and following best practices to create an error-free input file.

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Selecting Material Models for the Simulation of Foams 

We seek to lay down a framework to help us understand the different behavioral classes of foams. Following a methodology that we previously applied to plastics, we will then attempt to propose the right LS-DYNA material models that best capture these behaviours. Guidelines for model selection will be presented as well as best practices for characterization. Limitations of existing material models will be discussed.

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Material Modeling and Mold Analysis 

We present a perspective on material modeling as applied to mold analysis requirements. Melt-solid transitions and the case for a unified material model are discussed, along with prediction of post-filling material behavior and shrinkage, and the impact of viscous heating on flow behavior and material degradation.

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Practical Issues in the Development and Implementation of Hyperelastic Models

Hyperelastic models are used extensively in the finite element analysis of rubber and elastomers. These models need to be able to describe elastomeric behavior at large deformations and under different modes of deformation. In order to accomplish this daunting task, material models have been presented that can mathematically describe this behavior [1]. There are several in common use today, notably, the Mooney-Rivlin, Ogden and Arruda Boyce. Each of these has advantages that we will discuss in this article. Further, we will examine the applicability of a particular material model for a given modeling situation.

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