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pro vyhledávání: '"Sahin, Tarik"'
This paper explores the application of physics-informed neural networks (PINNs) to tackle forward problems in 3D contact mechanics, focusing on small deformation elasticity. We utilize a mixed-variable formulation, enhanced with output transformation
Externí odkaz:
http://arxiv.org/abs/2412.09022
In this study, we investigate the potential of fast-to-evaluate surrogate modeling techniques for developing a hybrid digital twin of a steel-reinforced concrete beam, serving as a representative example of a civil engineering structure. As surrogate
Externí odkaz:
http://arxiv.org/abs/2405.08406
Publikováno v:
In Journal of Open Innovation: Technology, Market, and Complexity March 2022 8(1)
Publikováno v:
In Journal of Open Innovation: Technology, Market, and Complexity June 2021 7(2)
How to manage disruptive innovation - a conceptual methodology for value-oriented portfolio planning
Autor:
Weinreich, Simon a, b, Şahin, Tarik a, Huth, Tobias a, Breimesser, Helmut b, Vietor, Thomas a
Publikováno v:
In Procedia CIRP 2021 100:403-408
Publikováno v:
Advanced Modeling & Simulation in Engineering Sciences; 5/3/2024, Vol. 11 Issue 1, p1-30, 30p
Akademický článek
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Autor:
von Danwitz, Max, Kochmann, Thank Thank, Sahin, Tarik, Wimmer, Johannes, Braml, Thomas, Popp, Alexander
Publikováno v:
PAMM: Proceedings in Applied Mathematics & Mechanics; Mar2023, Vol. 22 Issue 1, p1-6, 6p