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Compas XR
Compas FAB
Impact Printing
Compas Timber
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 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 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.

Publications
GIR Dataset: A Geometry and Real Impulse Response Dataset

Data-Driven Acoustic Design of Diffuse Surfaces Using Self-Organizing Maps

Visualization methods for big and high-dimensional acoustic data

Computational Design and Evaluation of Acoustic Diffusion Panels for the Immersive Design Lab

A Data Acquisition Setup for Data Driven Acoustic Design

Credits:
Gramazio Kohler Research, ETH Zurich
Achilleas Xydis, Dr. Romana Rust, Gonzalo Casas, Dr. Beverly Ann Lytle

Laboratory for Acoustics / Noise Control Empa
Kurt Eggenschwiler, Dr. Kurt Heutschi

Strauss Electroacoustic GmbH
Jürgen Strauss

Swiss Data Science Center (SDSC)
Dr. Fernando Perez-Cruz, Dr. Nathanaël Perraudin


Support: Michael Lyrenmann, Philippe Fleischmann (Robotic Fabrication Lab, ETH Zurich)
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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