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AIXD: AI-eXtended Design
AI-Augmented Architectural Design
AR Timber Assemblies
Architectural Design with Conditional Autoencoders
Integrated 3D Printed Facade
Think Earth SP7
Robotic Plaster Spraying
Additive Manufactured Facade
Human-Machine Collaboration
Timber Assembly with Distributed Architectural Robotics
Eggshell Benches
Eggshell
CantiBox
Autonomous Dry Stone
RIBB3D
Data Driven Acoustic Design
Mesh Mould Prefabrication
Data Science Enabled Acoustic Design
Thin Folded Concrete Structures
FrameForm
Adaptive Detailing
Deep Timber
Robotic Fabrication Simulation for Spatial Structures
Jammed Architectural Structures
RobotSculptor
Digital Ceramics
On-site Robotic Construction
Mesh Mould Metal
Smart Dynamic Casting and Prefabrication
Spatial Timber Assemblies
Robotic Lightweight Structures
Mesh Mould and In situ Fabricator
Complex Timber Structures
Spatial Wire Cutting
Robotic Integral Attachment
Mobile Robotic Tiling
YOUR Software Environment
Aerial Construction
Smart Dynamic Casting
Topology Optimization
Mesh Mould
Acoustic Bricks
TailorCrete
BrickDesign
Echord
FlexBrick
Additive processes
Room acoustics

Data Science Enabled Acoustic Design for Digital Fabrication in Architecture, ETH Zurich, 2018-2021
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.

Credits:
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

Copyright 2024, Gramazio Kohler Research, ETH Zurich, Switzerland
Gramazio Kohler Research
Chair of Architecture and Digital Fabrication
ETH Zürich HIB E 43
Stefano-Franscini Platz 1 / CH-8093 Zurich

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