|About this Abstract
||7th World Congress on Integrated Computational Materials Engineering (ICME 2023)
||Towards Interoperability: Digital Representation of a Material Specific Characterization Method
||Bernd Bayerlein, Ghezal Ahmad Zia, Markus Schilling, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Birgit Skrotzki
|On-Site Speaker (Planned)
Certain metallic materials gain better mechanical properties through controlled heat treatments. In age-hardenable aluminum alloys, the strengthening mechanism is based on the controlled formation of nanometer sized precipitates, which hinder dislocation movement. Analysis of the microstructure and especially the precipitates by transmission electron microscopy allows identification of precipitate types and orientations. Dark-field imaging is often used to image the precipitates and quantify their relevant dimensions.
The present work aims at the digital representation of this material-specific characterization method. Instead of a time-consuming, manual image analysis, a digital approach is demonstrated. The integration of an exemplary digital workflow for quantitative precipitation analysis into a data pipeline concept is presented. Here ontologies enable linking of contextual information to the resulting output data in a triplestore. Publishing digital workflow and ontologies ensures the reproducibility of the data. The semantic structure enables data sharing and reuse for other applications and purposes, demonstrating interoperability.