<div class="csl-bib-body">
<div class="csl-entry">Fricke, C. D., Steinbrecher, I., Wolff, D., Popp, A., & Elgeti, S. (2023). Optimization of fiber-reinforced materials to passively control strain-stress response. In <i>10th GACM Colloquium on Computational Mechanics from Young Scientists from Academia and Industry</i> (pp. 86–86). http://hdl.handle.net/20.500.12708/190948</div>
</div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/190948
-
dc.description.abstract
The intricate and nonlinear nature of material behavior, characterized by a progressively changing stress-strain relationship, is a fundamental and indispensable property governing the behavior of numerous mechanical systems. Examples of these mechanical systems include rubber components in automobile suspensions and engine mounts, soft tissues and organs in bio-mechanics and medical engineering, as well as packaging materials such as foam, paper, and plastics. Components used for the construction of these mechanical systems often need to meet specific stiffness requirements which can be influenced by the composition of the employed material, see Steinbrecher et al.
[Computational Mechanics, 69 (2022)].
On the macro or micro level, such materials can often be classified as fiber-reinforced materials, i.e., thin and long fibers embedded inside a matrix material. One way to control the stress-strain relationship of fiber-reinforced materials is to alter the geometry of the reinforcements, thus creating passive materials with a highly nonlinear stress-strain response. This can be a viable method for the development of optimized system components or meta-materials.
This method can be explored with a single beam embedded in a softer matrix. If the embedded beam is straight, the stress increase would be approximately linear with increasing strain. Bending the beam inside the matrix will lower the starting stress rate. The stress rate increases until the encased beam is straight, at which point the stress rate will not increase further. By manipulating the initial geometry of the beam, the evolution of the strain rate can be influenced.
Previously, Reinforcement Learning based shape optimization has been used to optimize structures in the context of fluid dynamics, see Fricke et al. [Advances in Computational Science and Engineering, 1 (2023)]. This approach is different from classical optimization methods, as it trains an agent to solve a specific task inside a defined problem set. While the training is computationally more expensive than a single optimization, the trained agent is able to optimize a problem inside the
learned problem set with less effort.
Applying the RL-based shape optimization method to the beam geometry, an agent is trained to identify optimal beam geometries for a set of starting stress rates and ending stress rates.
en
dc.language.iso
en
-
dc.subject
Shape Optimization
en
dc.subject
Reinforcement Learning
en
dc.subject
Fiber reinforced composites
en
dc.title
Optimization of fiber-reinforced materials to passively control strain-stress response
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
University of Bundeswehr Munich, Germany
-
dc.contributor.affiliation
RWTH Aachen University, Aachen, Germany
-
dc.contributor.affiliation
University of Bundeswehr Munich, Germany
-
dc.description.startpage
86
-
dc.description.endpage
86
-
dc.rights.holder
It is openly accessible, but does not define a license so that why I said "not public".
Link to the one I found: https://colloquia.gacm.de/fileadmin/Media_Colloquia/GACM2023/Book_GACM_2023_01.pdf
-
dc.type.category
Abstract Book Contribution
-
tuw.booktitle
10th GACM Colloquium on Computational Mechanics from Young Scientists from Academia and Industry
-
tuw.researchTopic.id
C4
-
tuw.researchTopic.id
X1
-
tuw.researchTopic.id
C1
-
tuw.researchTopic.name
Mathematical and Algorithmic Foundations
-
tuw.researchTopic.name
Beyond TUW-research foci
-
tuw.researchTopic.name
Computational Materials Science
-
tuw.researchTopic.value
30
-
tuw.researchTopic.value
40
-
tuw.researchTopic.value
30
-
tuw.publication.orgunit
E317-01 - Forschungsbereich Leichtbau
-
dc.description.numberOfPages
1
-
tuw.author.orcid
0000-0002-9495-2285
-
tuw.author.orcid
0000-0002-8820-466X
-
tuw.author.orcid
0000-0002-4474-1666
-
tuw.event.name
10th GACM Colloquium on Computational Mechanics from Young Scientists from Academia and Industry 2023
en
tuw.event.startdate
10-09-2023
-
tuw.event.enddate
13-09-2023
-
tuw.event.online
On Site
-
tuw.event.type
Event for scientific audience
-
tuw.event.place
Wien
-
tuw.event.country
AT
-
tuw.event.presenter
Fricke, Clemens David
-
wb.sciencebranch
Maschinenbau
-
wb.sciencebranch
Informatik
-
wb.sciencebranch
Sonstige Technische Wissenschaften
-
wb.sciencebranch.oefos
2030
-
wb.sciencebranch.oefos
1020
-
wb.sciencebranch.oefos
2119
-
wb.sciencebranch.value
70
-
wb.sciencebranch.value
20
-
wb.sciencebranch.value
10
-
item.fulltext
no Fulltext
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
item.languageiso639-1
en
-
item.cerifentitytype
Publications
-
item.openairetype
conference paper
-
item.grantfulltext
none
-
crisitem.author.dept
E317-01-2 - Forschungsgruppe Struktur- und Werkstoffsimulation
-
crisitem.author.dept
University of Bundeswehr Munich, Germany
-
crisitem.author.dept
E317-01 - Forschungsbereich Leichtbau
-
crisitem.author.dept
University of Bundeswehr Munich, Germany
-
crisitem.author.dept
E317-01 - Forschungsbereich Leichtbau
-
crisitem.author.orcid
0000-0002-9495-2285
-
crisitem.author.orcid
0000-0002-8820-466X
-
crisitem.author.orcid
0000-0002-4474-1666
-
crisitem.author.parentorg
E317-01 - Forschungsbereich Leichtbau
-
crisitem.author.parentorg
E317 - Institut für Leichtbau und Struktur-Biomechanik
-
crisitem.author.parentorg
E317 - Institut für Leichtbau und Struktur-Biomechanik