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...
November 15, 2017 | by Altair Engineering | views 2895
Simulation uncertainties arise from different assumptions made in model creation. Mid-stage software validations improve confidence and optimize the design of additively manufactured aerospace components.
Mechanical Aerospace and Defense Structural Analysis Papers Validation 3D Printing
November 01, 2017 | by DatapointLabs | views 2198
Propos recueillis par Olivier Guillon : Pierre-Pascal Bouf représente désormais DatapointLabs en France et plus largement en Europe si nécessaire. Celui-ci nous fait part de l’ambition de l’entreprise spécialiste dans les essais de matériaux et dévoile sa stratégie dont le succès passera inévitablement, selon lui, par une approche de partenariat avec ses clients, en particulier ceux de l’automobile.
October 25, 2017 | by Datapoint Newsletters | views 3754
CAETestBench Validation, Universal TestPaks, Matereality Analyzer Enhancement
Rheology Thermal Mechanical Moldflow LS-DYNA Abaqus ANSYS Moldex3D SIGMASOFT SOLIDWORKS NX Nastran PAM-CRASH RADIOSS Simpoe-Mold Newsletters Validation Matereality
October 07, 2017 | by DatapointLabs | views 3729
Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing, and digital twinning. Simulations use mathematical models to replicate physical reality. Verification and validation (V&V) is an important step for high-fidelity simulation. While verification is a way to check the accuracy of these models, factors such as simulation settings, element type, mesh size, choice of material model, material parameter conversion process, quality and suitability of material property data used can have a large impact on simulation quality. Validation presents a means to check simulation accuracy against a physical experiment. These validations are a valuable tool to measure solver accuracy prior to use in product development. Confidence is gained that the simulation replicates real-life physical behavior.
August 02, 2017 | by DatapointLabs | views 4136
The modeling of material behavior for injection molded plastics is a vital step for good simulation results. We detail the types of material data needed by various injection-molding simulation programs, factors that can affect simulation quality including test techniques and process variables such as moisture content. The case of fiber filled plastics is covered along with the extension to structural analysis applications.
Plastics Visco-elastic Rate Dependency Injection Molding Nonlinear Material Models Structural Analysis Moldflow LS-DYNA Abaqus Moldex3D DIGIMAT SIGMASOFT Multi-CAE Molding Simpoe-Mold Presentations Validation
July 20, 2017 | by Datapoint Newsletters | views 4647
Upcoming Events, Technical Team Expands
Plastics Injection Molding Structural Analysis Moldflow LS-DYNA ANSYS Moldex3D DIGIMAT Multi-CAE Molding Newsletters Validation ANSA
June 14, 2017 | by Hubert Lobo | views 3355
DatapointLabs Technical Center for Materials has a mission to strengthen the materials core of manufacturing enterprises by facilitating the use of new materials, novel manufacturing processes, and simulation-based product development. A whole-process approach is needed to address the role of materials in this context.
Mechanical Plastics Rubbers Metals Hyperelastic Nonlinear Material Models Structural Analysis ANSYS Validation 3D Printing Matereality Materials Information Management
June 12, 2017 | by DatapointLabs | views 3104
Physically accurate simulation is a requirement for initiatives such as late-stage prototyping, additive manufacturing and digital twinning. The use of mid-stage validation has been shown to be a valuable tool to measure solver accuracy prior to use in simulation. Factors such as simulation settings, element type, mesh size, choice of material model, the material model parameter conversion process, quality and suitability of material property data used can all be evaluated. These validations do not use real-life parts, but instead use carefully designed standardized geometries in a controlled physical test that probes the accuracy of the simulation. With this a priori knowledge, it is possible to make meaningful design decisions. Confidence is gained that the simulation replicates real-life physical behavior. We present three case studies using different solvers and materials, which illustrate the broad applicability of this technique.
Mechanical Plastics Rubbers Metals Structural Analysis LS-DYNA Abaqus ANSYS Research Papers Presentations Validation 3D Printing
May 31, 2017 | by Matereality | views 4296
Systems simulations involve material models for many materials. Since different kinds of simulations may be performed ranging from NVH to crash, such material files exist for a variety of solvers. It is a difficult task to ensure the self-consistency of material nomenclature for all these cases, such that the materials information is current and the right material files are used for each material. We present a system where materials information is uniformly deployed to CAD and CAE from libraries set up in Matereality. Consistent naming conventions and unit systems are used. Material files are linked to source material data for reference and traceability.
Papers Presentations ANSA Matereality Materials Information Management
May 10, 2017 | by Matereality | views 4910
We describe a new software component that takes into consideration the unique multi-variate nature of LS-DYNA material models. Rate-dependent models require adjustment and tuning of many material parameters to fit the rate-dependent tensile properties. Drawing upon a robust back-end data model, a graphical user interface provides drag and drop capability to allow the user to perform tasks such as model extrapolation beyond tested data, modulus change, rate dependency tuning and failure criteria adjustment while assuring self-consistency of the underlying material model. Unit system conversions are also facilitated, eliminating error and ensuring that material inputs to simulation correctly reflect the intent of the CAE analyst. The utility of the Matereality CAE modelers is illustrated with examples for LS-DYNA material models MAT_019, MAT_024 and MAT_089 LCSR.
Mechanical Rate Dependency Yielding/Failure analysis LS-DYNA Papers Presentations Matereality
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