An Investigation into Form Blending in Architecture Through Generative Form-Finding and Optimization Procedures: A form-finding methodology
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Date
2024
Authors
Wilhelm Neusser
Mauricio Morales-Beltran
Işik Ülkün Neusser
Manfred Berthold
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Architectural Geometry, Design Method, Form-blending, Form-finding, Generative Design, Multi-objective Optimization
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26841843
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210246378&partnerID=40&md5=c52b222c23fab5e428683221972564ce;ʻForm-blendingʼ is a computational design tool rooted in the animation industry and utilized by 3D programs originally developed for cartoon films. At the turn of the millennium architects and designers started utilizing ʻform-blendingʼ to design gradual shapes. However since these form-blended geometries per se have their genesis rooted in merging irregular patterns they do not necessarily embrace structural principles. Thus the use of ʻform-blendingʼ tools does not guarantee geometries adhere to any generic structural rationale. To address this problem a comparison discussing the pros and cons of optimization methods and tools regarding their potential for integration into ʻform-blendingʼ was initiated. The outcome of this process suggested the development of a methodology incorporating discretization finite element model and multi-objective optimization in connection with tools such as ʻform-blending' to generate geometries with structural logic. This methodology aims to enable architects and designers to receive structural feedback during the design process and to generate variants based on structural objectives. In a case study employing form-blended shapes the methodology was tested to evaluate the methodologyʼs applicability and performance. The results exhibited form-blended geometry based on structural rationale and form-finding principles. Thus supporting architects with a methodology to employ computational tools such as ʻform blendingʼ to design and generate variants of shapes based on a structural logic for further structural development. © 2024 Elsevier B.V. All rights reserved.
https://gcris.yasar.edu.tr/handle/123456789/8266
https://gcris.yasar.edu.tr/handle/123456789/8266
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