Computational data-driven based optimization of tribological performance of graphene filled glass fiber reinforced polymer composite using machine learning approach-Reference-Cited by-同舟云学术

Computational data-driven based optimization of tribological performance of graphene filled glass fiber reinforced polymer composite using machine learning approach

Published:2022 Issue: Volume:66 Page:3838-3846
ISSN:2214-7853
Container-title:Materials Today: Proceedings
language:en
Short-container-title:Materials Today: Proceedings

Author:

Sourabh K Singh K,Kumar Santosh,Singh K.K.

Publisher

Elsevier BV

Subject

General Medicine

Reference32 articles.

1. Tribological behaviour of fibre-reinforced thermoset polymer composites: A review;Kumar;Proc. Inst. Mech. Eng., Part L: J Mater.: Design Appl.,2020

2. Materials for Engineering;Martin,2006

3. Recent progress of reinforcement materials: a comprehensive overview of composite materials;Rajak;J. Mater. Res. Technol.,2019

4. Reference Module in Materials Science and Materials Engineering;Naslain,2016

5. Derek Hull, T.W. Clyne, An Introduction to Composite Materials, Cambridge University Press, n.d.

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