Machine learning as a surrogate for FEM: Predicting mechanical properties of tyresList of abbreviations

Accurately characterizing the mechanical properties of tyre materials remains a critical challenge due to their heterogeneous composition and anisotropic behaviour. This study introduces a comprehensive modelling pipeline that integrates composite-informed Finite Element Methods (FEM) with supervise...

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Bibliografische gegevens

Hoofdauteurs:	Yang Pei, Bing Han, Dileep Kumar, Scott Adams, Sui Yang Khoo, Michael Norton, Abbas Z. Kouzani
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	KeAi Communications Co., Ltd. 2025-10-01
Reeks:	Advanced Industrial and Engineering Polymer Research
Onderwerpen:	FEM Machine learning Surrogate modelling Composite materials Young's modulus Tyres
Online toegang:	http://www.sciencedirect.com/science/article/pii/S2542504825000399
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