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Timber Assembly with Distributed Architectural Robotics
Eggshell
Human-Machine Collaboration
Robotic Plaster Spraying
Autonomous Dry Stone
Data Driven Acoustic Design
COMPAS FAB
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 Driven Acoustic Design , ETH Zurich, 2018-2022
PhD research
This research aims to develop a novel approach to performance-driven acoustic design of sound diffusive surfaces. This approach will enable designers to explore and design a plethora of acoustically-informed surfaces without requiring expert knowledge in acoustics.
It focuses on collecting, analysing, and classifying impulse responses from computationally designed and physically prototyped surfaces to build a training set for machine learning applications. A state of the art automated robotic setup (go to the project) was used to create the GIR Dataset, an extensive collection of real impulse responses and three-dimensional diffusive surfaces. Unsupervised machine learning techniques and custom data visualisation methods are used to analyse and explore the GIR Dataset. The outcome of this research aims to simplify the design-simulation-evaluation process, bringing acoustics closer to the architecture practice and enabling more acoustic aware designs.

Get the GIR Dataset Renkulab

Publications
Xydis Achilleas, Nathanaël Perraudin, Romana Rust, Kurt Heutschi, Gonzalo Casas, Oksana Riba Grognuz, Kurt Eggenschwiler, Matthias Kohler, and Fernando Perez-Cruz. 2021. ‘GIR Dataset: A Geometry and Real Impulse Response Dataset’. Zenodo. Dataset

Rust Romana, Achilleas Xydis, Christian Frick, Jürgen Strauss, Christoph Junk, Jelle Feringa, Fabio Gramazio, and Matthias Kohler. 2021. ‘Computational Design and Evaluation of Acoustic Diffusion Panels for the Immersive Design Lab’. In Towards a New, Configurable Architecture - Proceedings of the 39th ECAADe Conference. pdf

Rust Romana, Achilleas Xydis, Kurt Heutschi, Nathanael Perraudin, Gonzalo Casas, Chaoyu Du, Jürgen Strauss, et al. 2021. ‘A Data Acquisition Setup for Data Driven Acoustic Design’. Building Acoustics, February, 1351010X20986901. Preprint PDF

Credits:
Gramazio Kohler Research, ETH Zurich

In cooperation with: Laboratory for Acoustics / Noise Control Empa, Strauss Electroacoustic GmbH, Swiss Data Science Center (SDSC)
Collaborators: Achilleas Xydis (project lead), Dr. Romana Rust, Gonzalo Casas, Dr. Beverly Ann Lytle, Kurt Eggenschwiler, Dr. Kurt Heutschi, Jürgen Strauss, Dr. Fernando Perez-Cruz, Dr. Nathanaël Perraudin, Michael Lyrenmann, Philippe Fleischmann

Copyright 2022, 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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