Graph-based tensile strength approximation of random nonwoven materials by interpretable regression

Nonwoven materials consist of random fiber structures. They are essential to diverse application areas such as clothing, insulation and filtering. A long term goal in industry is the simulation-based optimization of material properties in dependence of the manufacturing parameters. Recent works deve...

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Detalhes bibliográficos

Principais autores:	Dario Antweiler, Marc Harmening, Nicole Marheineke, Andre Schmeißer, Raimund Wegener, Pascal Welke
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2022-06-01
coleção:	Machine Learning with Applications
Assuntos:	Nonwoven fiber material Manufacturing Textile fabrics Material property prediction Graph representation Interpretable machine learning
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2666827022000214
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