| id |
caadria2024_173 |
| authors |
Gu, Sijia, Wu, Yufei, Gao, Tianyi and Yuan, Philip F. |
| year |
2024 |
| title |
A Modulus-Based Encoding Method for Continuous Gradient Pattern in Architectural Knitted Fabrics |
| doi |
https://doi.org/10.52842/conf.caadria.2024.3.151
|
| 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. 151–160 |
| summary |
In the realm of lightweight materials in architecture, knitting as a discrete additive method has enabled the creation of functionally graded material (FGM). For the current research in encoding methods for knitting FGM materials, researchers tend to focus on a limited number of surface transitions to study localized material traits. However, designing at an architectural scale demands multiple hierarchical structures for smooth transitions due to amplified performance differences, resulting in a complex system. Thus, organizing knitting units during encoding becomes crucial. This paper proposes a modulus-based encoding method for architectural knitting FGM materials, accommodating various surface types to create continuous gradient patterns. Based on the Grasshopper platform and STOLL machines, the method translates 3D models into machine encoding by using BMP (Bitmap) graphics. The method was successfully applied in a workshop in Tongji University. This research explores the fabrication of knitting FGM materials with multi-patterns in architecture, aiming to inspire innovative applications of fabrics in architecture. |
| keywords |
structural grading model, functionally graded material, knitted fabrics, encoding method, architectural design |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (836,782 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/11/17 22:05 |
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