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Calibration and Validation of Epoxy Adhesive Joints: Evaluation of LAW36 and LAW59 in Radioss

This 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.

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Material Testing and Calibration Strategies for Material Models of Polymers, Foams, and Composite Materials

The 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.

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Comparison of Calibration Strategies for Material Models of Polymers, Foam, and Composite Materials

The 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.

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Beyond Standards: Material Testing and Processing for Successful Simulations of Polymeric Materials (LAW76)

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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