| id |
acadia22_704 |
| authors |
Xydis, Achilleas; Du, Chaoyu; Rust, Romana; Gramazio, Fabio; Kohler, Matthias |
| year |
2022 |
| title |
Visualization Methods for Big and High-Dimensional Acoustic Data |
| source |
ACADIA 2022: Hybrids and Haecceities [Proceedings of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 704-713. |
| summary |
This research proposes a novel approach for interactive visualizations of acoustic datasets for architects and non-acoustic experts. It introduces a series of simple acoustic properties for users with basic knowledge of acoustics and describes methods for low- and high-dimensional data visualizations. It describes the computational workflow and uses a design scenario to demonstrate the proposed visualizations. Finally, it discusses the challenges of developing such methods, their advantages, limitations, and future work. |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (3,107,760 bytes) |
| references |
Content-type: text/plain
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 Data-Driven Acoustic Design of Diffuse Surfaces Using Self-Organizing Maps
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| last changed |
2024/02/06 14:04 |
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