<div class="csl-bib-body">
<div class="csl-entry">Schwaighofer, M., Königsberger, M., Lukacevic, M., & Füssl, J. (2026). A Deep Learning-Enhanced Continuum Micromechanics Framework for Nonlinear Homogeization of Composites with Nonellipsoidal Inclusions Geometries. In <i>96th Annual Meeting of the Intertnational Association of Applied Mathematics and Mechanics : March16th - 20th, 2026 Stuttgart (Germany) : Book of Abstracts</i> (pp. 221–221). http://hdl.handle.net/20.500.12708/227969</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/227969
-
dc.language.iso
en
-
dc.subject
Macroscopic Mechanical Response
en
dc.subject
Finite Element-based Eshelby Analysis
en
dc.subject
Nonellipsoidal Inclusions Geometries
en
dc.title
A Deep Learning-Enhanced Continuum Micromechanics Framework for Nonlinear Homogeization of Composites with Nonellipsoidal Inclusions Geometries
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.description.startpage
221
-
dc.description.endpage
221
-
dc.type.category
Abstract Book Contribution
-
tuw.booktitle
96th Annual Meeting of the Intertnational Association of Applied Mathematics and Mechanics : March16th - 20th, 2026 Stuttgart (Germany) : Book of Abstracts
-
tuw.researchTopic.id
C1
-
tuw.researchTopic.name
Computational Materials Science
-
tuw.researchTopic.value
100
-
tuw.publication.orgunit
E202-02 - Forschungsbereich Struktursimulation und Ingenieurholzbau
