November 21, 2014 | by DatapointLabs | views 4656
Thermoplastic materials are one of the largest categories of materials to be injection molded. Simulation of the injection molding process requires sophisticated and exact material properties to be measured. This presentation will discuss the testing required to characterize a material for use in SIGMASOFT, as well as the significance of material model parameters. Differences in testing methodology for amorphous and semi-crystalline polymers will be covered, along with step-by-step implementation into the software to produce a successful injection molding simulation simulation.
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Plastics
Electonics/Electrical
Injection Molding
Nonlinear Material Models
Structural Analysis
SIGMASOFT
Presentations
April 30, 2014 | by DatapointLabs | views 4313
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
April 04, 2014 | by Datapoint Newsletters | views 5309
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
February 13, 2014 | by DatapointLabs | views 4396
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
October 29, 2013 | by DatapointLabs | views 4478
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
July 21, 2010 | by DatapointLabs | views 4415
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
May 16, 2008 | by DatapointLabs | views 4697
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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Plastics
Rubbers
Foams
Metals
Aerospace and Defense
Automotive
Biomedical
Consumer Products
Energy and Petroleum
Electonics/Electrical
Industrial Goods
CAE Vendor/Supplier
Packaging
Home Appliances
Blow Molding
Extrusion
Injection Molding
Nonlinear Material Models
Moldflow
Composites
Presentations
Gels
Oils/Lubricants
Waxes