Methods for the Prediction and Specification of Functionally Graded Multi-Grain Responsive Timber Composites

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The paper presents design-integrated methods for high-resolution specification
and prediction of functionally graded wood-based thermal responsive composites,
using machine learning. The objective is the development of new circular design
workflow, employing robotic fabrication, in order to predict fabrication files
linked to material performance and design requirements, focused on application
for intrinsic responsive and adaptive architectural surfaces. Through an
experimental case study, the paper explores how machine learning can form a
predictive design framework where low-resolution data can solve material
systems at high resolution. The experimental computational and prototyping
studies show that the presented image-based machine learning method can be
adopted and adapted across various stages and scales of architectural design and
fabrication. This in turn allows for a design-per-requirement approach that
optimizes material distribution and promotes material economy
OriginalsprogEngelsk
TiteleCAADe Conference Proceedings 2020
Antal sider10
Vol/bind2
UdgivelsesstedBerlin
ForlageCAADe
Publikationsdato2020
Udgave1
Sider585-594
ISBN (Trykt)978-9-49120-721-1
StatusUdgivet - 2020
BegivenhedEducation and research in Computer Aided Architectural Design in Europe: Anthropologic – Architecture and Fabrication in the cognitive age - Online, Berlin, Tyskland
Varighed: 16 sep. 202017 sep. 2020
Konferencens nummer: 38
https://www.ecaade2020.tu-berlin.de/

Konference

KonferenceEducation and research in Computer Aided Architectural Design in Europe
Nummer38
LokationOnline
LandTyskland
ByBerlin
Periode16/09/202017/09/2020
Internetadresse
NavnProceedings of the International Online Conference on Education and Research in Computer Aided Architectural Design in Europe
ISSN2684-1843

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