Yildirim, Erinç

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Profile URL
https://gcris.yasar.edu.tr/handle/123456789/12875
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Job Title
Araş.Gör.
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Main Affiliation
01.01.10.02. Mimarlık Bölümü
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Current Staff
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ORCID ID
0000-0001-8093-3991
Scopus Author ID
57218139034
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WoS Researcher ID
GZG-1684-2022
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1st International Conference on Optimization-Driven Architectural Design OPTARCH 20191
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    Weight and Material Optimization of Scissor-hinge Linkages According to Given Span Length
    (Elsevier B.V., 2020) Yenal Akgün; Feray Maden; Erinç Yildirim; Yildirim, Erinç; Akgün, Yenal; Maden, Feray; N.D. Lagaros , K.M. Abdalla , G.C. Marano , M.C. Phocas , R. Al Rousan
    Scissor-hinge linkages are one type of deployable structures which are mostly used in architectural and engineering applications due to their transformation capabilities and the advantages of ease of erection and dismantling. For hundreds of years these linkages have been used in wide range of applications such as deployable roof structures bridges shells pavilions emergency shelters furniture design and satellite equipment. Scissor-hinge linkages have different primary units depending on the geometry of the bars and the location of the pivot point which are called as polar translational and angulated. Geometry and dimensions of these primary elements directly affect the geometry and the weight of the whole structure. This study aims to investigate the relationship between the span length geometry of the primary units cross section of the bars and the material of the scissor-hinge linkages by means of genetic algorithms. In detail a structural and geometric optimization is made in order to obtain the lightest geometric configuration for the given span lengths while keeping the structural strength and stability by altering typology dimensions number of the primary units and material parameters. To achieve that a multi-objective genetic algorithm based optimization approach is utilized. Generative model is created in Grasshopper® parametric design software. The structural performances of the generated solutions are evaluated with the help of Karamba3D that is a parametric structural tool for Grasshopper. Optimization of the problem is performed via multi objective genetic optimization plug-in named Octopus. © 2020 Elsevier B.V. All rights reserved.