We are pleased to announce that the topic “Improved Hyperelastic Material Characterization Using Measurement Data Pre-Processing“, presented by our team at the 2024 DAS Conference in Gdańsk, is now available in written form. The joint work, authored by Zoltán Kovács and András Aninger from Econ Engineering and Szabolcs Berezvai from the Budapest University of Technology and Economics, marks another milestone in our commitment to advancing experimental mechanics and simulation technologies.
At the 2024 DAS Conference in Gdańsk, our team presented the topic of Improved Hyperelastic Material Characterization Using Measurement Data Pre-Processing.
The presentation is now available on The Journal of Theoretical and Applied Mechanics (JTAM) as a complete written study, authored by Zoltan Kovács and András Aninger from Econ Engineering, and Szabolcs Berezvai from the Budapest University of Technology and Economics.
Summary of the topic
The mechanical characterization of elastomers remains a challenging area in engineering. While finite element solvers offer a wide range of hyperelastic models, selecting the most suitable one for a specific application is not straightforward. Our newly published paper introduces a methodology for high-fidelity hyperelastic parameter fitting, specifically tailored for elastomers.
A key innovation is the pre-processing module, which analyzes measurement data from stress-strain curves to help select the optimal hyperelastic model and provide physically consistent initial parameter values for the fitting process. The approach was validated using both the classic Treloar dataset and experimental data from a nitrile butadiene rubber (NBR) specimen.
Key Findings
- The pre-processing step significantly improves the accuracy of parameter fitting, especially for complex models with many parameters.
- The method provides better initial values for model parameters, reducing uncertainty and improving the uniqueness of the fit.
- While the approach did not always reduce fitting runtimes for simpler models, it offers substantial benefits for more complex cases, such as compressible or viscoelastic models.
- The methodology assists engineers in choosing the most appropriate material model, enhancing the reliability of simulation results.
Download the complete study in PDF.
Looking Ahead
This publication underscores eCon Engineering’s dedication to innovation in simulation and experimental mechanics. We believe our work will support engineers and researchers in achieving more accurate and reliable material characterizations, ultimately driving advancements in product development and engineering design.
For more information or questions about the study, or about other related topics, please feel free to contact our team!
