Towards interoperability: Digital representation of a material specific characterization method
- 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 ontologiesCertain 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.…
Autor*innen: | Bernd BayerleinORCiD |
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Koautor*innen: | Ghezal Ahmad Zia, Markus SchillingORCiD, J. Waitelonis, P. v. Hartrott, T. Hanke, Birgit SkrotzkiORCiD |
Dokumenttyp: | Vortrag |
Veröffentlichungsform: | Präsentation |
Sprache: | Englisch |
Jahr der Erstveröffentlichung: | 2023 |
Organisationseinheit der BAM: | 5 Werkstofftechnik |
5 Werkstofftechnik / 5.2 Metallische Hochtemperaturwerkstoffe | |
DDC-Klassifikation: | Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten |
Freie Schlagwörter: | Data Management; Digtial Representation; FAIR; Ontology; Reproducibility; Semantic Interoperability |
Themenfelder/Aktivitätsfelder der BAM: | Material |
Material / Materialdesign | |
Veranstaltung: | TMS - 7th World Congress on Integrated Computational Materials Engineering (ICME) |
Veranstaltungsort: | Orlando, Florida, USA |
Beginndatum der Veranstaltung: | 21.05.2023 |
Enddatum der Veranstaltung: | 25.05.2023 |
Verfügbarkeit des Dokuments: | Datei im Netzwerk der BAM verfügbar ("Closed Access") |
Datum der Freischaltung: | 30.05.2023 |
Referierte Publikation: | Nein |
Eingeladener Vortrag: | Nein |