Strengthening the materials core of manufacturing enterprises
Materials in simulation
Material specifications define properties for incoming materials to meet required criteria. We present software that manages creation of material specifications, input of properties and material composition; and provides a way to evaluate qualification per specification. While it is designed for OEM/Tier n environments, it is also applicable for materials suppliers.
Read full postPlastics 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.
Read full postThe 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.
Read full postAs 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.
Read full postThere 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.
Read full postToday, 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.
Read full postDatapointLabs' 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.
Read full postThe testing of materials for use in crash and safety simulations and the conversion of test data into material models is a process that is not well standardized in the industry. Consequently, CAE users face uncertainty and risk in this process that can have a negative impact on simulation quality. In this workshop, we present approaches currently used in the US for the gathering of high quality test data plus the acclaimed Matereality CAE Modeler software that is used to transform high strain-rate data into crash material cards.
Read full postWe present a methodology for DIGIMAT users to perform the DIGIMAT MX reverse engineering process to obtain material parameter inputs for crash, elasto-plastic, creep and visco-elasticity. The injection-molding process used involves a standardized plaque geometry with fully developed flow, with test specimens taken from a specific plaque location. A standardized testing procedure is applied and the resulting DIGIMAT MX inputs are handled in a streamlined data stream, which saves time and improves the reliability of the reverse engineering process. The DIGIMAT MX reverse engineering itself can be performed as a service in collaboration with e-Xstream. This gives the user a speedy and tightly controlled process for performing complex finite element analysis with filled plastics
Read full postThe 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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