Record link: 
http://hdl.handle.net/20.500.12708/229905
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Title: 
Towards Patient-Specific Stent Designs: Developing Design Strategies Using Reinforcement Learning
en
Citation: 
Fricke, C. D., Steinbrecher, I., Wolff, D., Key, F., Popp, A., & Elgeti, S. (2026, July 20). Towards Patient-Specific Stent Designs: Developing Design Strategies Using Reinforcement Learning [Conference Presentation]. 17th World Congress on Computational Mechanics & 10th European Congress on Computational Methods in Applied Sciences and Engineering (WCCM-ECCOMAS 2026), München, Germany. http://hdl.handle.net/20.500.12708/229905
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Publication Type: 
Presentation - Conference Presentation
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Language: 
English
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Authors: 
Fricke, Clemens David 
Steinbrecher, Ivo 
Wolff, Daniel 
Key, Fabian 
Popp, Alexander 
Elgeti, Stefanie 
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Organisational Unit: 
E317-01-1 - Forschungsgruppe Numerische Analyse- und Designmethoden 
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Date (published): 
20-Jul-2026
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Event name: 
17th World Congress on Computational Mechanics & 10th European Congress on Computational Methods in Applied Sciences and Engineering (WCCM-ECCOMAS 2026) 
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Event date: 
19-Jul-2026 - 24-Jul-2026
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Event place: 
München, Germany
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Keywords: 
Reinforcement Learning; Shape Optimization; stent design; Computational Mechanics; designed material
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Project title: 
Autonomer Konstruktionsassistent zur Aneurysmenreperatur: PIN4090124 (FWF - Österr. Wissenschaftsfonds) 
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Research Areas: 
Modeling and Simulation: 80%
Computational Materials Science: 10%
Beyond TUW-research focus: 10%
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Science Branch: 
2030 - Maschinenbau: 40%
2119 - Sonstige Technische Wissenschaften: 50%
1010 - Mathematik: 10%
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Appears in Collections:
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