| id |
caadria2024_524 |
| authors |
Castelo-Branco, Renata, Caetano, Ines and Leitao, António |
| year |
2024 |
| title |
Algorithmic design explained: Decomposing parametric 3D problems into 2D visual illustrations |
| source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 3, pp. 9–18 |
| doi |
https://doi.org/10.52842/conf.caadria.2024.3.009
|
| summary |
Algorithmic Design (AD) is a promising approach that merges two distinct processes - design thinking and computational thinking. However, it requires converting design concepts into algorithmic descriptions, which not only deviates from architecture's visual nature, but also tends to result in unstructured programs that are difficult to understand. Sketches or diagrams can help explain AD programs by capitalizing on their geometric nature, but they rapidly become outdated as designs progress. In ongoing research, an automatic illustration system was proposed to reduce the effort associated with updating 2D diagrams as ADs evolve. This paper discusses the ability of this system to improve the comprehension of AD programs that represent complex 3D architectural structures. To understand how to best explain parametric 3D models using 2D drawings, this research explores problem decomposition techniques, applying them in the visual documentation of two case studies, where illustration aids different comprehension scenarios: illustrating for future use, and illustrating while designing as part of the AD process. |
| keywords |
algorithmic design, automatic illustration, design documentation, design representation |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (941,248 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/11/17 22:05 |
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