On the Data-Driven Modeling of Reactive Extrusion

On the Data-Driven Modeling of Reactive Extrusion

This paper analyzes the ability of different machine learning techniques, able to operate in the low-data limit, for constructing the model linking material and process parameters with the properties and performances of parts obtained by reactive polymer extrusion. The use of data-driven approaches...

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Bibliographic Details
Main Authors: Ruben Ibañez, Fanny Casteran, Clara Argerich, Chady Ghnatios, Nicolas Hascoet, Amine Ammar, Philippe Cassagnau, Francisco Chinesta
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Fluids
Subjects:
reactive extrusion
data-driven
machine learning
artificial engineering
polymer processing
digital twin
Online Access:https://www.mdpi.com/2311-5521/5/2/94

Internet

https://www.mdpi.com/2311-5521/5/2/94

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