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Methode zur Massengenerierung von Topologieoptimierungsmodellen

Hygrell, Erik Andreas (2023) Methode zur Massengenerierung von Topologieoptimierungsmodellen. Bachelor's, TU Berlin.

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Topology optimization is a common technique to generate optimal structures with respect to given loads and constraints. In this thesis, a method for the creation of large numbers of topology optimizations is proposed. The method variates the parameters of optimization models by assigning multiple fixed states which the parameters can take, and then automatically creating an optimization model for each possible combination of these parameter states, similar to a factorial design as it known from design of experiments. Each optimization model is then submitted to Altairs solver OptiStruct for optimization. In this thesis, it is described which types of optimization models are supported, and which parameters are available for automatic variation. Five test runs of the program were performed, and their results analyzed with respect to their similarity to each other, which showed that the program is capable of generating optimization results that are in general not very similar to each other.

Item URL in elib:https://elib.dlr.de/197236/
Document Type:Thesis (Bachelor's)
Title:Methode zur Massengenerierung von Topologieoptimierungsmodellen
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Number of Pages:103
Institution:TU Berlin
Department:Fachgebiet Strukturmechanik und Strukturberechnung
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 - RoSto - Rolling Stock
Location: Stuttgart
Institutes and Institutions:Institute of Vehicle Concepts > Vehicle Architectures and Lightweight Design Concepts
Deposited By: Gomes Alves, Christian
Deposited On:28 Sep 2023 11:53
Last Modified:28 Sep 2023 11:53

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