Machine learning models for forward and inverse structure–property relationships in complex materials: a case study on damage tolerant dual-phase steels
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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Rheinisch-Westfälische Technische Hochschule Aachen, Dissertation, 2024
- Schlagwort
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Mikrostruktur
Maschinelles Lernen
Mikromechanik
Dualphasenstahl
Inverses Problem
- Ereignis
-
Veröffentlichung
- (wo)
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Aachen
- (wer)
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Universitätsbibliothek der RWTH Aachen
- (wann)
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2024
- Urheber
- Beteiligte Personen und Organisationen
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Raabe, Dierk
Diehl, Martin
- DOI
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10.18154/RWTH-2024-04639
- URN
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urn:nbn:de:101:1-2407170133348.984690255343
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:53 MESZ
Datenpartner
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Beteiligte
- Kusampudi, Navyanth
- Raabe, Dierk
- Diehl, Martin
- Universitätsbibliothek der RWTH Aachen
Entstanden
- 2024
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