Predicting and steering performance in architectural materials

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningpeer review

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Abstract

This paper presents the prototyping of new methods by which functionally gradedmaterials can be specified and produced. The paper presents a case studyexploring how machine learning can be used to train a model in order to predictfabrication files from formalised design requirements. By using knit as a modelfor material fabrication, the paper outlines the making of new cyclical designmethods employing machine learning in which simpler prototypical materials actsas input for more complex graded materials. A case study - Ombre - showcasesthe implementation of this workflow and results and perspectives are discussed.
OriginalsprogEngelsk
TitelArchitecture in the Age of the 4th Industrial Revolution : Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019
RedaktørerJosé Pedro Sousa, Joäo Pedro Xavier, Goncalo Castro Henriques
Antal sider10
UdgivelsesstedPorto
Publikationsdato2019
Sider485-494
Artikelnummer150
StatusUdgivet - 2019
BegivenhedeCAADe: Architecture in the Age of the 4th Industrial Revolution - University of Porto (FAUP), Faculty of Architecture, Porto, Portugal
Varighed: 11 sep. 201913 sep. 2019
https://ecaadesigradi2019.arq.up.pt/

Konference

KonferenceeCAADe
LokationUniversity of Porto (FAUP), Faculty of Architecture
Land/OmrådePortugal
ByPorto
Periode11/09/201913/09/2019
Internetadresse
NavnECAADE SIGRADI 2019 Architecture in the age of the 4th Industrial revolution

Emneord

  • Computation
  • CNC Knit
  • Machine learning
  • Textile
  • Material behaviour
  • Digital fabrication

Kunstnerisk udviklingsvirksomhed (KUV)

  • Nej

Citationsformater