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Data-driven exploration and continuum modeling of dislocation networks

Sudmanns, M.; Bach, J.; Weygand, D.; Schulz, K.

The microstructural origin of strain hardening during plastic deformation in stage II deformation of face-centered cubic (fcc) metals can be attributed to the increase in dislocation density resulting in a formation of dislocation networks. Although this is a well known relation, the complexity of dislocation multiplication processes and details about the formation of dislocation networks have recently been revealed by discrete dislocation dynamics (DDD) simulations. It has been observed that dislocations, after being generated by multiplication mechanisms, show a limited expansion within their slip plane before they get trapped in the network by dislocation reactions. This mechanism involves multiple slip systems and results in a heterogeneous dislocation network, which is not reflected in most dislocation-based continuum models. We approach the continuum modeling of dislocation networks by using data science methods to provide a link between discrete dislocations and the continuum level. For this purpose, we identify relevant correlations that feed into a model for dislocation networks in a dislocation-based continuum theory of plasticity. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000122738
Veröffentlicht am 29.08.2020
DOI: 10.1088/1361-651X/ab97ef
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Materialien - Computational Materials Science (IAM-CMS)
Institut für Baustatik (IBS)
Institut für Programmstrukturen und Datenorganisation (IPD)
Young Investigator Network (YIN)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 09.2020
Sprache Englisch
Identifikator ISSN: 0965-0393, 1361-651X
KITopen-ID: 1000122738
Erschienen in Modelling and simulation in materials science and engineering
Verlag IOP Publishing
Band 28
Heft 6
Seiten Art. Nr.: 065001
Vorab online veröffentlicht am 19.06.2020
Schlagwörter crystal plasticity, continuum dislocation dynamics, dislocation networks, data science, data-driven modeling
Nachgewiesen in Web of Science
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