Strengthening the materials core of manufacturing enterprises
Materials in simulation
This presentation compares Radioss adhesive material models, LAW36 and LAW59, with the objective of assessing their predictive capabilities for epoxy-based structural adhesives.
Read full postThis work presents a comparative study of adhesive material models LAW36 and LAW59, in Radioss, with the objective of assessing their predictive capabilities for epoxy-based structural adhesives. The investigation focuses on simulating stress distributions, fracture energies, and failure mechanisms in joints of varying adhesive thicknesses (0.1, 0.2, and 0.5 mm). A comprehensive experimental program supports numerical analysis, including bulk tensile, Thick adherend shear test, and Mode I fracture toughness tests, based on ISO 527-2, ISO 11003-2, and EN 6033 standards, respectively. An additional validation test replicating multi-mode loading conditions is incorporated to establish transferability of the calibrated models to realistic applications. Numerical models employ solid elements for adhesive layers and shell elements for metallic adherends, with mesh refinement in adhesive regions to resolve local stress gradients. Displacement-controlled loading is applied to reproduce tensile and shear conditions, enabling extraction of stress-strain responses, fracture energies, and failure patterns. Model calibration is performed against experimental data using fracture toughness, failure strain, and maximum stress as reference parameters. Comparative evaluation is conducted with quantitative error metrics to assess accuracy and computational cost. The results aim to identify the most reliable adhesive law for joint-level simulations, providing guidance for model selection in structural applications.
Read full postPresented at JOURNÉE TECHNIQUE COLLAGE hosted by Applus+ Rescoll, October 14, 2025; Bordeaux, France.
Read full postThe accurate calibration of materials models is crucial for simulating the behavior of materials across various industries, including automotive, aerospace, and consumer goods. With the increasing complexity of modern materials, particularly polymers, foams, and composite materials, developing reliable and efficient calibration strategies is more important than ever. This paper presents a comprehensive comparative analysis of calibration strategies for material models applied to these materials, focusing on the challenges and best practices for each material class.
Read full postThe accurate calibration of materials models is crucial for simulating the behavior of materials across various industries, including automotive, aerospace, and consumer goods. With the increasing complexity of modern materials, particularly polymers, foams, and composite materials, developing reliable and efficient calibration strategies is more important than ever. This paper presents a comprehensive comparative analysis of calibration strategies for material models applied to these materials, focusing on the challenges and best practices for each material class.
Read full postOur 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.
Read full postPresented by Marian Bulla, Altair Engineering, at the CARHS Automotive CAE Grand Challenge 2020.
Read full postKeynote address delivered at NAFEMS seminar on "Material Properties in Structural Calculation: Modeling, Calibration, Simulation & Optimization."
Read full postMulti-scale material models are being increasing applied for high level simulation of complex materials such as UD layups, fabric laminate composites, fiber-filled plastics. These models require data inputs from a variety of material tests which are then assembled into models used in the finite element solvers. We present an infrastructure for the digitalization of such information, where the required material data are collected including a process for maintaining traceability and consistency of the source data. Information about the compositional characteristics and processing history are captured. Built-in software modules or external client tools can be used for calibration of material models with the resulting material file linked to the source data. The accuracy of the reduced order model can be checked by running a validation simulation against a physical test. Models can be published and released into a master CAE materials library output where they can be used to model such materials for a variety of target solvers. This process improves the reliability and accuracy of composites simulation.
Read full postPhysically 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.
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