<div class="csl-bib-body">
<div class="csl-entry">Fricke, C. D., Luxner, M., Peyker, L., Mitrovic, L., & Pettermann, H. (2024, June 3). <i>Machine-Learning-Based Surrogate Material Models For Elasto-Plasticity And Elasto-Damage</i> [Conference Presentation]. ECCOMAS 2024 - 9th European Congress on Computational Methods in Applied Sciences and Engineering, Lissabon, Portugal.</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/199193
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dc.description.abstract
Constitutive material models are used in the Finite Element Method (FEM) to determine the material response at each integration point. For complex materials, e.g., microstructured materials like composites, it is often necessary to fully resolve the microscale to reliably deduce the materials’ mechanical responses. One popular approach is FE^2 , where at each integration point of the macroscopic FEM model a microscopic FEM model is solved concurrently. This is however computationally extremely expensive, especially for three-dimensional structures with material non-linearities. The cost of solving the microscopic FEM models can be avoided by using a surrogate material model instead. For example, simple models can be used as surrogates for linear-elastic responses of the microscopic material. In contrast, if non-linear responses including dissipative mechanisms need to be considered, defining surrogate models is not as straightforward. Especially, if the material model should also be capable of predicting multi-directional loading paths with unloading. For such use cases, data-driven surrogate material models can be trained by utilizing training data produced from FEM-simulation results. In detail, for a body-centered cubic lattice material, microscale elasto-plastic simulations are conducted. The resulting machine learning (ML)-based surrogate of the lattice material is tested by comparing the corresponding macroscopic simulation results to fully-resolved simulation results. As a second use-case, the developed methodology is employed to convert an existing phenomenological analytical material model into an ML-based surrogate material model. This pre-existing material model has implemented elasto=damage mechanisms for unidirectional-reinforced composite materials, that are to be modeled in the surrogate material model as well.
en
dc.language.iso
en
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dc.subject
Surrogate Material Model
en
dc.subject
Machine Learning
en
dc.subject
Elasto-Plasticity
en
dc.subject
Solid Mechanics
en
dc.subject
Finite Element Method
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dc.title
Machine-Learning-Based Surrogate Material Models For Elasto-Plasticity And Elasto-Damage
en
dc.type
Presentation
en
dc.type
Vortrag
de
dc.contributor.affiliation
Luxner Engineering ZT GmbH
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dc.type.category
Conference Presentation
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tuw.researchTopic.id
C4
-
tuw.researchTopic.id
C1
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tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.name
Computational Materials Science
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tuw.researchTopic.value
5
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tuw.researchTopic.value
95
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tuw.publication.orgunit
E317-01-2 - Forschungsgruppe Struktur- und Werkstoffsimulation
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tuw.author.orcid
0000-0002-9495-2285
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tuw.author.orcid
0000-0001-7162-5989
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tuw.event.name
ECCOMAS 2024 - 9th European Congress on Computational Methods in Applied Sciences and Engineering
en
tuw.event.startdate
03-06-2024
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tuw.event.enddate
07-06-2024
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Lissabon
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tuw.event.country
PT
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tuw.event.presenter
Fricke, Clemens David
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wb.sciencebranch
Maschinenbau
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wb.sciencebranch
Sonstige Technische Wissenschaften
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wb.sciencebranch.oefos
2030
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wb.sciencebranch.oefos
2119
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wb.sciencebranch.value
80
-
wb.sciencebranch.value
20
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item.grantfulltext
none
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item.openairecristype
http://purl.org/coar/resource_type/c_18cp
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item.fulltext
no Fulltext
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item.cerifentitytype
Publications
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item.languageiso639-1
en
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item.openairetype
conference paper not in proceedings
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crisitem.author.dept
E317-01-2 - Forschungsgruppe Struktur- und Werkstoffsimulation
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crisitem.author.dept
E317-01 - Forschungsbereich Leichtbau
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crisitem.author.dept
E317-01-2 - Forschungsgruppe Struktur- und Werkstoffsimulation
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crisitem.author.orcid
0000-0002-9495-2285
-
crisitem.author.orcid
0000-0001-7162-5989
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crisitem.author.parentorg
E317-01 - Forschungsbereich Leichtbau
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crisitem.author.parentorg
E317 - Institut für Leichtbau und Struktur-Biomechanik
