The recipient of the FAIR Data and Software Award Lower Saxony 2024 in the "Dataset" category will present insights into the published and award-winning data as well as their research in this talk. You can learn more about the FAIR Data and Software Award Lower Saxony 2024 at the homepage of FDM-NDS: https://fdm-nds.de/index.php/fair_award_2024/.
Abstract of the talk:
The calibration of material models is becoming increasingly important both in structural health monitoring and in the experimental characterization of new materials. Due to the high information density, calibration based on full-field data is attracting increasing interest. Together with research groups at TU Clausthal and ETH Zürich, we investigated parametric physics-informed neural networks for calibration of material models using full-field displacement data. In order to validate the method using real data, we conducted experiments and measured full-field displacement data using digital image correlation. In alignment with the FAIR principles, we have published the data together with our results and our research code. We look forward to sharing more about our research and the published data set in this talk.
Registration is not required, but highly recommended, as it allows us to contact you in case of any changes and to share event materials with you.
The event is organized by the State Initiative Research Data Management Lower Saxony (FDM-NDS). FDM-NDS is a collaborative project under the umbrella of Hochschule.digital Niedersachsen and is funded through zukunft.niedersachsen, a funding program of the Lower Saxony Ministry of Science and Culture (MWK) and the Volkswagen Foundation.
