Abstract

In recent years, the application of space-frame structures on large-scale freeform designs has significantly increased, due to their lightweight configuration and the freedom of design they offer. However, this has introduced a level of complexity into their construction, as doubly-curved designs require non-uniform configurations. This paper proposes a novel computational workflow that reduces the construction complexity of freeform space-frame structures, by minimizing variability in its joints. Space-frame joints are evaluated according to their geometry, and clustered for production in compliance with the tolerance requirements of the selected fabrication process. This provides a direct insight into the level of customization required and the associated construction complexity. A subsequent geometry optimization of the space-frame’s depth then minimizes the number of different joint groups required. The variables of the optimization are defined in relation to the structure’s curvature, providing a direct link between the structure’s geometry and the optimization process. Through the application of a control surface, the dimensionality of the design space is drastically reduced, rendering this method applicable to large-scale projects. A case study of an existing structure of complex geometry is presented, and this method achieves a significant reduction in the construction complexity in a robust and computationally efficient way.
Original languageEnglish
Number of pages18
JournalInternational Journal of Architectural Computing
Early online date9 Jan 2020
DOIs
Publication statusE-pub ahead of print - 9 Jan 2020

Cite this

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title = "Rationalization of Freeform Space-Frame Structures for Fabrication: Reducing variability in the joints",
abstract = "In recent years, the application of space-frame structures on large-scale freeform designs has significantly increased, due to their lightweight configuration and the freedom of design they offer. However, this has introduced a level of complexity into their construction, as doubly-curved designs require non-uniform configurations. This paper proposes a novel computational workflow that reduces the construction complexity of freeform space-frame structures, by minimizing variability in its joints. Space-frame joints are evaluated according to their geometry, and clustered for production in compliance with the tolerance requirements of the selected fabrication process. This provides a direct insight into the level of customization required and the associated construction complexity. A subsequent geometry optimization of the space-frame’s depth then minimizes the number of different joint groups required. The variables of the optimization are defined in relation to the structure’s curvature, providing a direct link between the structure’s geometry and the optimization process. Through the application of a control surface, the dimensionality of the design space is drastically reduced, rendering this method applicable to large-scale projects. A case study of an existing structure of complex geometry is presented, and this method achieves a significant reduction in the construction complexity in a robust and computationally efficient way.",
author = "Antiopi Koronaki and Paul Shepherd and Mark Evernden",
year = "2020",
month = "1",
day = "9",
doi = "10.1177/1478077119894881",
language = "English",
journal = "International Journal of Architectural Computing",
issn = "1478-0771",
publisher = "Multi-Science Publishing Co. Ltd",

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T2 - Reducing variability in the joints

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AU - Shepherd, Paul

AU - Evernden, Mark

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N2 - In recent years, the application of space-frame structures on large-scale freeform designs has significantly increased, due to their lightweight configuration and the freedom of design they offer. However, this has introduced a level of complexity into their construction, as doubly-curved designs require non-uniform configurations. This paper proposes a novel computational workflow that reduces the construction complexity of freeform space-frame structures, by minimizing variability in its joints. Space-frame joints are evaluated according to their geometry, and clustered for production in compliance with the tolerance requirements of the selected fabrication process. This provides a direct insight into the level of customization required and the associated construction complexity. A subsequent geometry optimization of the space-frame’s depth then minimizes the number of different joint groups required. The variables of the optimization are defined in relation to the structure’s curvature, providing a direct link between the structure’s geometry and the optimization process. Through the application of a control surface, the dimensionality of the design space is drastically reduced, rendering this method applicable to large-scale projects. A case study of an existing structure of complex geometry is presented, and this method achieves a significant reduction in the construction complexity in a robust and computationally efficient way.

AB - In recent years, the application of space-frame structures on large-scale freeform designs has significantly increased, due to their lightweight configuration and the freedom of design they offer. However, this has introduced a level of complexity into their construction, as doubly-curved designs require non-uniform configurations. This paper proposes a novel computational workflow that reduces the construction complexity of freeform space-frame structures, by minimizing variability in its joints. Space-frame joints are evaluated according to their geometry, and clustered for production in compliance with the tolerance requirements of the selected fabrication process. This provides a direct insight into the level of customization required and the associated construction complexity. A subsequent geometry optimization of the space-frame’s depth then minimizes the number of different joint groups required. The variables of the optimization are defined in relation to the structure’s curvature, providing a direct link between the structure’s geometry and the optimization process. Through the application of a control surface, the dimensionality of the design space is drastically reduced, rendering this method applicable to large-scale projects. A case study of an existing structure of complex geometry is presented, and this method achieves a significant reduction in the construction complexity in a robust and computationally efficient way.

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