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Topology Optimization: AI approach for mesh segmentation

Bornachot, Yohan and Gomes Alves, Christian (2020) Topology Optimization: AI approach for mesh segmentation. Project thesis, ENSTA Paris.

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Abstract

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.

Item URL in elib:https://elib.dlr.de/140277/
Document Type:Thesis (Project thesis)
Title:Topology Optimization: AI approach for mesh segmentation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Bornachot, YohanUNSPECIFIEDUNSPECIFIED
Gomes Alves, ChristianChristian.GomesAlves (at) dlr.dehttps://orcid.org/0000-0002-0897-6951
Date:2020
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:54
Status:Published
Keywords:Artificial Intelligence (AI), Topology Optimization (TO), Finite Element Model (FEM), Beams, Gaussian Mixture Model (GMM), Spectral Clustering
Institution:ENSTA Paris
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Rail Transport
DLR - Research area:Transport
DLR - Program:V SC Schienenverkehr
DLR - Research theme (Project):V - NGT BIT
Location: Stuttgart
Institutes and Institutions:Institute of Vehicle Concepts
Deposited By: Gomes Alves, Christian
Deposited On:12 Jan 2021 15:06
Last Modified:12 Jan 2021 15:06

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