Dezembro 2019 vol. 7 num. 1 - 37 Education and Research in Computer Aided Architectural Design in Europe and XXIII Iberoamerican Society of Digital Graphics, Joint Conference (N. 1)

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Predicting and steering performance in architectural materials

Predicting and steering performance in architectural materials

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

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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.

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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.

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DOI: 10.5151/proceedings-ecaadesigradi2019_150

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Como citar:

Sinke, Yuliya; Thomsen, Mette; Nicholas, Paul; Tamke, Martin; Gatz, Sebastian; "Predicting and steering performance in architectural materials", p. 485-494 . In: Proceedings of 37 eCAADe and XXIII SIGraDi Joint Conference, “Architecture in the Age of the 4Th Industrial Revolution”, Porto 2019, Sousa, José Pedro; Henriques, Gonçalo Castro; Xavier, João Pedro (eds.). São Paulo: Blucher, 2019.
ISSN 2318-6968, DOI 10.5151/proceedings-ecaadesigradi2019_150

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