| id |
acadia20_198 |
| authors |
Sinke Baranovskaya, Yuliya; Tamke, Martin; Ramsgaard Thomsen, Mette |
| year |
2020 |
| title |
Simulation and Calibration of Graded Knitted Membranes |
| doi |
https://doi.org/10.52842/conf.acadia.2020.2.198
|
| source |
ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 198-207. |
| summary |
The grading of knit changes its geometrical performance and steers membrane expansion. However, knit possesses challenges of material predictability and digital simulation, due to its multiscalar complexity and anisotropic properties. Taking as a challenge the lack of digital solutions incorporating CNC-knit performance into the design model, this paper presents a novel approach for the design-integrated simulation of graded knit, informed by an empirical dataset analysis in combination with genetic optimization algorithms. Here the simulation design tool reflects the differences of industrially knitted textile panel behavior through digital mesh grading. Diversified fabric stiffness is achieved by intertwining the yarn into variegated stitch types that steer the textile expansion under load. These are represented digitally as zoned quad meshes with each segment assigned a stiffness value. Mesh stiffness values are optimized by minimizing the distance between the point clouds and the digital mesh, which are documented through deviation colored maps. This work concludes that design properties用attern topology, stitch ratio, pattern density用lay an important role in textile panel performance under load. Stiffness values derived from the optimization are higher for shallower designs and lower for the deeper cones. |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (9,790,329 bytes) |
| references |
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