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Data Science Enabled Acoustic Design for Digital Fabrication in Architecture, ETH Zurich, 2018-2021
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This research project studied the relationship between diffusive surface structures and their acoustic performance. The surfaces were computationally designed to resemble common architectural fabrication typologies (brick walls, rubble stone walls, slated stone walls), measuring approximately 6x6 meters. Material and construction parameters particular to each typology were coded in a geometry generation algorithm and utilized to generate various surfaces. The surfaces were 3D printed on a 1:10 scale using binder-jet 3D printing and sprayed with two layers of paint to increase their sound reflectivity. An automated robotic setup was employed to record the impulse responses in front of these surfaces. The robotic arms, one equipped with a speaker (source) and the other with a microphone (receiver), acted as dynamic measuring devices recording the sound reflection from the 3D printed surfaces.
The outcome of this research is the Geometry and real Impulse Response Dataset (GIR Dataset), the first dataset containing physically recorded impulse responses corresponding to particular 3D structures.
The dataset is released under the GNU General Public License v3.0 and can be downloaded from the Renku repository.
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Credits:
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Gramazio Kohler Research, ETH Zurich
In cooperation with: Laboratory for Acoustics / Noise Control Empa, Strauss Electroacoustic GmbH, Swiss Data Science Center (SDSC) Research programme: Swiss Data Science Center (SDSC) Collaborators: Dr. Romana Rust (project lead), Achilleas Xydis (PhD student), Gonzalo Casas, Kurt Eggenschwiler, Dr. Kurt Heutschi, Jürgen Strauss, Dr. Fernando Perez-Cruz, Dr. Nathanaël Perraudin, Michael Lyrenmann, Philippe Fleischmann
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