September 26, 2024 | by DatapointLabs | views 233
Our presentation, “Beyond Standards: Material Testing and Processing for Successful Simulations of Polymeric Materials (LAW76)”, focuses on the Semi-Analytical Model for Polymers (SAMP), a material law developed for simulating complex polymer behavior in industries like automotive and aerospace. SAMP integrates strain-rate dependencies and a damage model for accurate predictions in crash and impact scenarios but faces limitations like slow convergence and the absence of a damage model that incorporates strain-rate and triaxiality dependencies. We emphasize the need to go beyond standardized testing, advocating for tailored tests that better reflect real-world conditions, such as varying strain rates, geometries, and environmental factors. This presentation also details a semi-automated calibration process for SAMP and BIQUAD models using iterative workflows to optimize simulation accuracy for tension, compression, shear, and impact tests. Ultimately, SAMP’s flexibility and predictive accuracy make it a powerful tool, but its successful implementation requires advanced knowledge, customized testing, and careful calibration to ensure stability and reliability in material simulations.
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Plastics
Yielding/Failure Analysis
Altair RADIOSS
Presentations
Validation
April 17, 2024 | by DatapointLabs | views 1576
Thermoplastic composites present a promising opportunity for innovation within the automotive sector, owing to their lightweight properties, durability, and recyclability. Our efforts concentrate on testing and developing models to accurately simulate the behavior of materials in automotive settings. By delivering precise simulation models, we empower manufacturers to gain deeper insights into the performance of these materials, thereby streamlining their incorporation into vehicle design and manufacturing workflows. This advancement ensures the effective utilization of thermoplastic composites, resulting in tangible advantages such as improved fuel efficiency, enhanced safety, and reduced environmental footprint across the automotive industry.
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Automotive
Nonlinear Material Models
Composites
Validation
July 11, 2023 | by Pablo Cruz | views 1131
This paper describes an engineering process to generate material cards for forefront crashworthiness CAE analysis that properly capture both plastic and fracture behaviour of car body structural metals. The main objective of the paper is to show that advanced plasticity approaches can be used without significantly increasing the complexity of the overall material characterization process. The paper is mainly centred in metals plastic characterization for shell elements although some important relationships with the fracture characterization will be also discussed.
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Metals
Automotive
Structural Analysis
LS-DYNA
May 22, 2023 | by Datapoint Newsletters | views 1877
DatapointLabs Founders Retire; Company Continues Focus on Materials in Simulation
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Thermal
Mechanical
Foams
Newsletters
Validation
May 15, 2023 | by DatapointLabs | views 1519
Simulations play a crucial role in engineering and material science, and their success heavily relies on the accuracy of input data. Material testing, data conversion, fitting, and formatting are essential steps in the simulation process. This conference will highlight the importance of material testing requirements that extend beyond ISO and ASTM standards to obtain reliable data for input into various common material models, such as Elastic-Plastic, Hyperelastic, and Rate Dependent models. The complexity of foam materials is shown through a case study of successful validation of polyurethane (PU) foam ball drop impact test using LAW 90. PU foams exhibit high deformation with rate dependency in compressive loading, as well as viscoelastic unloading behavior. Proper handling of input test data and critical settings in simulation setup are crucial for accurate results. The case study will showcase our streamlined approach to successful simulation of foam materials, including challenges and limitations of current material models.
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Mechanical
Foams
Hyperelastic
Rate Dependency
Altair RADIOSS
Validation
September 22, 2022 | by DatapointLabs | views 1573
Material characterization considerations for SIGMASOFT simulations using thermoplastic and thermoset materials.
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Rheology
Thermal
Mechanical
Plastics
Rubbers
Injection Molding
SIGMASOFT
January 31, 2022 | by Datapoint Newsletters | views 2787
DatapointLabs Achieves Nadcap® Accreditation
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Thermal
Mechanical
Plastics
Composites
Quality
October 05, 2021 | by Pablo Cruz | views 2538
A deep understanding of advanced material plasticity and fracture is one of the cornerstones of mechanical engineering to overcome present and future challenges in the automotive industry with respect to lightweight multi-material body solutions.
The correct material law selection may imply a design lightweight efficiency improvement of between 10% and 20% depending on the material, component geometry, manufacturing technology and performance requirements. The accurate implementation of the plastic behaviour becomes mandatory when material fracture is a central design parameter.
In this paper, the authors propose a clear process to experimentally measure and assess how far uniaxially tested materials are from pure isochoric plastic behaviour. This process will be named Non-isochoric Plasticity Assessment (NPA). In order to illustrate the process, NPA will be applied to actual experimental results of representative automotive metals and thermoplastics.
Material plastic dilation behaviour is studied. A general description is provided regarding plasticity theory concepts required for the usage of non-isochoric plasticity material laws. An approach for the validation of the experimental input data consistency for both SAMP-1 and SAMP-Light material laws is also proposed.
The overall approach is finally applied and validated on an extruded aluminium and a thermoplastic showing a proper level of correlation between CAE and experimental results for shell-based FE-models.
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Plastics
Metals
Automotive
Structural Analysis
LS-DYNA
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