Bornachot, Yohan und Gomes Alves, Christian (2020) Topology Optimization: AI approach for mesh segmentation. Projektarbeit, ENSTA Paris.
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Kurzfassung
Topology Optimization is a major concern in the conceptual part of a product since it allows optimal structures to be created. Knowing the Finite Element Model process that is used, it is important to be able to analyze the results. Artificial intelligence could possibly make a difference and help the user in its decisions regarding the structure. Mesh segmentation theoretically allows a mesh to be divided into relevant parts. To count the number of beams in such a structure, different mesh segmentation and clustering techniques are presented and applied to separate beams from each other. Taking the Topology Optimization result as an input, to prepare the data, and to apply clustering afterward are the goals of this internship.
elib-URL des Eintrags: | https://elib.dlr.de/140277/ | ||||||
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Dokumentart: | Hochschulschrift (Projektarbeit) | ||||||
Titel: | Topology Optimization: AI approach for mesh segmentation | ||||||
Autoren: |
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Datum: | 2020 | ||||||
Open Access: | Nein | ||||||
Seitenanzahl: | 54 | ||||||
Stichwörter: | Artificial Intelligence (AI), Topology Optimization (TO), Finite Element Model (FEM), Beams, Gaussian Mixture Model (GMM), Spectral Clustering | ||||||
Institution: | ENSTA Paris | ||||||
DLR - Schwerpunkt: | Verkehr | ||||||
DLR - Forschungsgebiet: | V SC Schienenverkehr | ||||||
Standort: | Stuttgart | ||||||
Institute & Einrichtungen: | Institut für Fahrzeugkonzepte |
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