Predicting and steering performance in architectural materials

Mette Ramsgaard Thomsen; Paul Nicholas; Martin Tamke; Sebastian Gatz; Yuliya Sinke

Predicting and steering performance in architectural materials

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer 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.

Originalsprog	Engelsk
Titel	Architecture 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
Redaktører	José Pedro Sousa, Joäo Pedro Xavier, Goncalo Castro Henriques
Antal sider	10
Udgivelsessted	Porto
Publikationsdato	2019
Sider	485-494
Artikelnummer	150
Status	Udgivet - 2019
Begivenhed	eCAADe: Architecture in the Age of the 4th Industrial Revolution - University of Porto (FAUP), Faculty of Architecture, Porto, Portugal Varighed: 11 sep. 2019 → 13 sep. 2019 https://ecaadesigradi2019.arq.up.pt/

Konference

Konference	eCAADe
Lokation	University of Porto (FAUP), Faculty of Architecture
Land/Område	Portugal
By	Porto
Periode	11/09/2019 → 13/09/2019
Internetadresse	https://ecaadesigradi2019.arq.up.pt/

Navn	ECAADE 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

Adgang til dokumentet

Predicting and steering performance in architectural materialsForlagets udgivne version, 15,4 MB

http://papers.cumincad.org/cgi-bin/works/BrowseTree=series=AZ/Show?ecaadesigradi2019_150

Citationsformater

Ramsgaard Thomsen, M., Nicholas, P., Tamke, M., Gatz, S., & Sinke, Y. (2019). Predicting and steering performance in architectural materials. I J. P. Sousa, J. P. Xavier, & G. Castro Henriques (red.), Architecture 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 (s. 485-494). Artikel 150. http://papers.cumincad.org/cgi-bin/works/BrowseTree=series=AZ/Show?ecaadesigradi2019_150

Ramsgaard Thomsen, Mette ; Nicholas, Paul ; Tamke, Martin et al. / Predicting and steering performance in architectural materials. Architecture 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. red. / José Pedro Sousa ; Joäo Pedro Xavier ; Goncalo Castro Henriques. Porto, 2019. s. 485-494 (ECAADE SIGRADI 2019 Architecture in the age of the 4th Industrial revolution).

@inproceedings{09aa13b7a81b48dc9b9f8e8e2168be2e,

title = "Predicting and steering performance in architectural materials",

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.",

keywords = "Computation, CNC Knit, Machine learning, Textile, Material behaviour, Digital fabrication, computational design, material specification, machine learning, convolution algorithm, knit",

author = "\{Ramsgaard Thomsen\}, Mette and Paul Nicholas and Martin Tamke and Sebastian Gatz and Yuliya Sinke",

year = "2019",

language = "English",

series = "ECAADE SIGRADI 2019 Architecture in the age of the 4th Industrial revolution",

pages = "485--494",

editor = "Sousa, \{Jos{\'e} Pedro\} and Xavier, \{Jo{\"a}o Pedro\} and \{Castro Henriques\}, Goncalo",

booktitle = "Architecture in the Age of the 4th Industrial Revolution",

note = "eCAADe : Architecture in the Age of the 4th Industrial Revolution ; Conference date: 11-09-2019 Through 13-09-2019",

url = "https://ecaadesigradi2019.arq.up.pt/",

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Ramsgaard Thomsen, M , Nicholas, P , Tamke, M , Gatz, S & Sinke, Y 2019, Predicting and steering performance in architectural materials. i JP Sousa, JP Xavier & G Castro Henriques (red), Architecture 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., 150, Porto, ECAADE SIGRADI 2019 Architecture in the age of the 4th Industrial revolution, s. 485-494, eCAADe, Porto, Portugal, 11/09/2019. <http://papers.cumincad.org/cgi-bin/works/BrowseTree=series=AZ/Show?ecaadesigradi2019_150>

Predicting and steering performance in architectural materials. / Ramsgaard Thomsen, Mette ; Nicholas, Paul ; Tamke, Martin et al.
Architecture 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. red. / José Pedro Sousa; Joäo Pedro Xavier; Goncalo Castro Henriques. Porto, 2019. s. 485-494 150 (ECAADE SIGRADI 2019 Architecture in the age of the 4th Industrial revolution).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

T1 - Predicting and steering performance in architectural materials

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AU - Nicholas, Paul

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AU - Gatz, Sebastian

AU - Sinke, Yuliya

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Computation

KW - CNC Knit

KW - Machine learning

KW - Textile

KW - Material behaviour

KW - Digital fabrication

KW - computational design

KW - material specification

KW - machine learning

KW - convolution algorithm

KW - knit

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Ramsgaard Thomsen M , Nicholas P , Tamke M , Gatz S , Sinke Y. Predicting and steering performance in architectural materials. I Sousa JP, Xavier JP, Castro Henriques G, red., Architecture 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. Porto. 2019. s. 485-494. 150. (ECAADE SIGRADI 2019 Architecture in the age of the 4th Industrial revolution).