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Knowmats is an informal repository of information related to materials and simulation. The information helps simulation professionals perform best-in-class simulation with a better understanding of how materials are represented in FEA and simulation. read more...


The Use of Digital Image Correlation (DIC) and Strain Gauges to Validate Simulation 

As part of Cornell University's mechanical engineering curriculum and study of classical beam theory, an aluminium beam is deformed to a specific load. Theoretical strains are calculated at certain points along the beam using beam theory, and then verified by using strain gauges placed at these points on the beam. This experiment is then extended to simulation of the same test setup in simulation software, where strains are analyzed at the same points. Discrepancies between the simulation, theory, and strain gauge results have often plagued the test, especially when incorporating more complex beam design. Through use of digital image correlation (DIC) it is possible to pinpoint some of the problem areas in the beam analysis and provide a better understanding of the localized strains that occur at any point in the deformed beam. The use of DIC provides a full field validation of simulation data, rather than a single spot check that strain gauges can provide. This validation technique helps to eliminate error that is associated with strain gauge placement and the possibility of missing strain hot spots that can arise when analyzing complex deformations or geometries.

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Plastics Metals Aerospace and Defense Automotive Biomedical Building Materials Consumer Products Material Supplier Toys/Sporting Goods Electonics/Electrical Industrial Goods CAE Vendor/Supplier Mold Maker/Designer Structural Analysis ANSYS Presentations


'Lego Man' - Accurate FEA of Engineering Plastics

This demonstration showing how to analyze plastic parts using finite element analysis was given by Patrick Cunningham at CAE Associates' Accurate FEA of Engineering Plastics seminar, held on October 14, 2014 in Tarrytown, NY.

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Plastics Plasticity Presentations


Thermoplastic Material Testing for Use in SIGMASOFT and the Effect of Moisture on PA 6/6

Thermoplastic materials are one of the largest categories of materials to be injection molded. Moisture-sensitive materials can lead to issues in the molding process. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation discusses the testing required to characterize a thermoplastic material for use in SIGMASOFT, as well as the effects of moisture on viscosity measurement of a moisture-sensitive material. Consequences of basing designs on wet or dry materials are covered. Implementation of material data into the software to produce a successful injection molding simulation simulation is described.

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Rheology Plastics CAE Vendor/Supplier Injection Molding Nonlinear Material Models SIGMASOFT Presentations


Experimental and Numerical Investigation of Fracture in Aluminium

"To assess the problem of containment after a blade-off accident in an aero-engine by numerical simulation the FAA has instigated a research effort concerning failure prediction in a number of relevant materials. Aluminium kicked off the program which involved an intensive testing program providing failure data under different states of stress, different strain rates and different temperatures. In particular split Hopkinson bars were used to perform dynamic punch tests on plates of different thicknesses allowing to investigate the transition between different failure modes such as petaling and plugging. Ballistic impact tests were performed at NASA GRC for the purpose of validation. This paper focuses on the numerical simulation effort and a comparison with experimental data is done. The simulations were performed with LS-DYNA and a tabulated version of the Johnson-Cook material law was developed in order to increase the generality, flexibility and user-friendliness of the material model."

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Mechanical Metals Yielding/Failure Analysis Aerospace and Defense High Speed Testing LS-DYNA Research Papers Validation


Handbook of Plastics Analysis: Book Review

Assurance of quality in raw materials, control over production, and a basic understanding of criteria for performance all require a sure and complete knowledge of analytical methods for plastics. The present volume organizes the vast world of plastics analysis into a relatively compact form. A plastics engineer will find familiar territory in such subjects as rheometry, differential scanning calorimetry, and measurement of thermal properties. Polymer physicists and chemists will be at home with spectroscopic analyses, liquid chromatography, and nuclear magnetic resonance. All these topics and many more are covered in twelve chapters written by an impressive array of experts drawn from industry and academia.

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Rheology Thermal Plastics Structural Analysis Book Review


Datapoint Newsletter: Archive

Links to Datapoint Newsletters published 1995-2007

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Newsletters


Simulating anisotropy with Ls-dyna in glass-reinforced, polypropylene-based components

Glass-fiber-reinforced polypropylene (GF PP) materials are increasingly being used by customers to replace metal and engineering polymers in structural automotive applications. Like all glass-fiber reinforced thermoplastics, GF PP products can show anisotropy caused by fiber orientation that is induced by the injection process. Taking into account fiber orientation in the simulations enables designers to improve the accuracy of the analyses. This can help prevent arbitrary choices and assumptions when setting material parameters, which become mandatory when an isotropic material law is used. The method proposed in this paper takes advantage of the availability within Ls-dyna of an anisotropic material law (MAT_103), which allows simplified modeling to address critical issues. This law was not developed to address the problem discussed here. Therefore, this paper illustrates a simplified approach. The presence of glass reinforced fibers is taken into account by running a mold-filling analysis, and then transferring the material flow orientation in to the structural simulation as a material angle. The dependence of the material failure strain on the material orientation can be also easily modeled through a user subroutine. Finally, the approach only requires simple material data based on basic tensile tests; the material law parameters are then identified through optimization techniques. Although this approach is based on some simplifying assumptions, its application is quick and can help the designer obtain more accurate results with respect to the traditional isotropic approach. A selection of validation tests is then proposed that show reliable predictions using limited additional computational effort.

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Mechanical Plastics Rate Dependency Automotive High Speed Testing LS-DYNA Research Papers


Creep modelling of Polyolefins using artificial neural networks

Notwithstanding the increasing demand for polymeric materials in an extraordinary variety of applications, the engineers have often only limited tools suitable for the design of parts made of polymers, both in terms of mathematical models and reliable material data, which together constitute the basis for a finite-elements based design. Within this context, creep modelling constitutes a clear example of the needs for a more refined approach. An accurate prediction of the creep behaviour of polymers would definitely lead to a more refined design and thus to a better performance of the polymeric components. However, a limited number of models is available within the f.e. codes, and when the model complexity increases, it becomes sometimes difficult fitting the models parameters to the experimental data. In order to predict the polymer creep behaviour, this paper proposes a solution based on artificial neural networks, where the experimental creep curves are used to determine the parameters of a neural network which is then simply implemented in an Abaqus user subroutine. This allows to avoid the implementation of a complex material law and also the difficulties related to match the experimental data to the model parameters, keeping easily into account the dependence on stress and temperature. After a discussion of the selection of the appropriate network and its parameters, an example of the application of this approach to polyolefins in a simplified test case is presented.

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Mechanical Plastics Automotive Biomedical Structural Analysis Abaqus Research Papers Validation


Characterization of Damage in Hyperelastic Materials Using Standard Test Methods and Abaqus

Over the past couple of decades, standard test methods and material models have existed for rubber-like materials. These materials were classified under the category of Hyperelastic materials. Well established physical test methods and computational procedures exist for the characterization of the material behavior in tension, compression, shear volumetric response, tear strength etc. However, effective modeling of the fracture behavior of hyperelastic materials using finite element techniques is very challenging. In this paper, we make an attempt to demonstrate the use of such standard test methods and the applicability of such test data for performing finite element analyses of complex nonlinear problems using Abaqus. Our goal is to demonstrate the effective use of standard physical test data to model multi-axial loading situations and fracture of hyperelastic materials through tear tests and indentation test simulations.

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Rubbers Material Supplier Industrial Goods Nonlinear Material Models Structural Analysis Abaqus Research Papers


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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Plastics Rubbers Foams Aerospace and Defense Automotive Biomedical Consumer Products Material Supplier Toys/Sporting Goods Electonics/Electrical Industrial Goods Packaging Home Appliances Presentations