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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...


Datapoint Newsletter: Summer '14, Volume 20.3

New Developments, Verification & Validation, Digimat-MX

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DIGIMAT Newsletters


Datapoint Newsletter: Late Spring '14, Volume 20.2a

Verification and Validation Are Focus of Technical Presentations at CAE Events, New Multi-CAE TestPaks® Deliver Data for Injection Molding and Crash Simulations,

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High Speed Testing Injection Molding Newsletters


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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Plastics Automotive Blow Molding High Speed Testing Injection Molding Nonlinear Material Models Structural Analysis Moldflow LS-DYNA Abaqus ANSYS Moldex3D DIGIMAT Multi-CAE Crash Multi-CAE Molding Multi-CAE Structural PAM-CRASH Presentations


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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Plastics Rubbers Foams Metals Automotive Biomedical Building Materials Consumer Products Energy and Petroleum Material Supplier Toys/Sporting Goods Electonics/Electrical Industrial Goods CAE Vendor/Supplier Mold Maker/Designer Nonlinear Material Models Structural Analysis Abaqus Composites SIMULIA Presentations


Datapoint Newsletter: Spring '14, Volume 20.2

Material Testing and Data Management to be Showcased at Technical Meetings Globally. DatapointLabs Expands Composite Testing to Meet Industry Demand. Supporting Innovation and Ingenuity in Our Local Schools

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Plastics Electonics/Electrical LS-DYNA Newsletters


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


Datapoint Newsletter: Winter '14, Volume 20.1

10 Years of Your Material Data, Available in Your Matereality® Database. Things You Can Do with Your Matereality Personal Material Database.

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Newsletters


Datapoint Newsletter: Fall '13, Volume 19.4

DatapointLabs on Inc. 5000 List. New Matereality Compare Module Automates Graphical Comparisons. Headquarters Facility Expands.

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Newsletters


Validating Simulation Using Digital Image Correlation 

There is interest in quantifying the differences between simulation and real life experimentation. This kind of work establishes a baseline for more complex simulations bringing a notion of traceability to the practice of CAE. We present the use of digital image correlation as a way to capture strain fields from component testing and compare these to simulation. Factors that are important in ensuring fidelity between simulation and experiment will be discussed.

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Plastics Aerospace and Defense Automotive Biomedical Material Supplier Electonics/Electrical CAE Vendor/Supplier Nonlinear Material Models Structural Analysis Abaqus Composites SIMULIA Presentations


Use of Digital Image Correlation to Obtain Material Model Parameters for Composites 

The development of material parameters for FEA is heavily reliant on precision material data that captures the stress-strain relationship with fidelity. While conventional methods involving UTMs and extensometers are quite adequate for obtaining such data on a number of materials, there are important cases where they have been known to be inadequate. The testing of composites to obtain directional properties remains a complex task because of the difficulty related to measuring these properties in different orientations. Digital Image Correlation (DIC) methods are able to capture the stress-strain relationship all the way to failure. In this paper, we combine DIC and conventional methods to measure directional properties of composites. We exploit the unique capability of DIC to retroactively place virtual strain gauges in areas of critical interest in the test specimen. Utilising an Iosipescu fixture, we measure shear properties of structured composites in a variety of orientations to compute the parameters of an orthotropic linear elastic material model. Model consistency is checked by validation using Abaqus.

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Aerospace and Defense Nonlinear Material Models Structural Analysis Abaqus Composites SIMULIA Research Papers