strengthening the materials core of manufacturing enterprises
DatapointLabs is now part of Applus laboratories

Materials in Simulation know your materials

Sort by: Date | Views

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: 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. full post


Datapoint Newsletter: Fall '13, Volume 19.4

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


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. full post

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. full post

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

Datapoint Newsletter: Summer '13, Volume 19.3

Digital Image Correlation Techniques Enhance Composite Testing Capability. Store and Manage Properties of Structured Composites with a Matereality® Database. full post

Automotive LS-DYNA Abaqus Composites Newsletters Validation

Datapoint Newsletter: Spring '13, Volume 19.2

Validating Simulation Using Digital Image Correlation. New TestPaks® for PlanetsX Injection Molding CAE Software Added to Test Catalog. full post

Abaqus PlanetsX Newsletters Validation

A Strategy for Material Testing and Data Management for the Automotive Industry 

Today, CAE is integrated with modern automotive product development. This creates new challenges for departments that support new product development. In the materials arena, the testing is elevated to much higher levels of sophistication and precision to accommodate the complex material models used in CAE. It is no longer simple matter to convert raw data into material model parameters. We present an end-to-end strategy that gives automakers a well managed pathway to transforming to simulation-based design. We operate a quick-turnaround expert material testing lab to support high-end CAE and product development. We provide a data management software designed specifically to capture and display material data of any complexity. The software can transform raw material data into material parameter files for most commonly used simulations. The CAE Modeler software is of adequate sophistication to fit equations to data, visualize material models along with raw data, and output material cards. Examples for high strain-rate crash material modeling will be presented. full post

Automotive CAE Vendor/Supplier Nonlinear Material Models Structural Analysis Presentations

Datapoint Newsletter: Winter '13, Volume 19.1

A Strategy for Material Testing and Data Management for the Automotive Industry. DatapointLabs Continues to Grow full post

Automotive Newsletters

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. full post

Plastics Nonlinear Material Models Structural Analysis LS-DYNA Composites Research Papers

Datapoint Newsletter: Fall '12, Volume 18.4

Inc. Magazine Features DatapointLabs. Book Release. Catalog Updates. full post