Year: 2019
Type: conference-paper
Abstract: This paper presents the prototyping of new methods by which functionally graded materials can be specified and produced.The paper presents a case study exploring how machine learning can be used to train a model in order to predict fabrication files from formalised design requirements.By using knit as a model for material fabrication, the paper outlines the making of new cyclical design methods employing machine learning in which simpler prototypical materials acts as input for more complex graded materials.A case study -Ombre -showcases the implementation of this workflow and results and perspectives are discussed.
Authors: Mette Thomsen, Paul Nicholas, Martin Tamke, Sebastian Gatz, Yuliya Sinke
Language: English
Subfield: Architecture
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W3000948014