On the Use of Machine Learning for Damage Assessment in Composite Structures: A Review

Ribeiro Junior, Ronny Francis; Gomes, Guilherme Ferreira

doi:10.1007/s10443-023-10161-5

Appl Compos Mater

2023

DOI: 10.1007/s10443-023-10161-5

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On the Use of Machine Learning for Damage Assessment in Composite Structures: A Review

Ronny Francis Ribeiro Junior,

Guilherme Ferreira Gomes

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2024

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Cited by 4 publications

References 117 publications

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A Review of Machine Learning for Progressive Damage Modelling of Fiber-Reinforced Composites

Loh,

Yeoh,

Raju

et al. 2024

Appl Compos Mater

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A Review of Machine Learning for Progressive Damage Modelling of Fiber-Reinforced Composites

Loh,

Yeoh,

Raju

et al. 2024

Appl Compos Mater

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The Development of Composites Materials: From Conventional to Innovative Uses

Hussain,

Praveen,

Ragavu

et al. 2024

E3S Web of Conf.

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This paper explores the evolution, development, and application of composite substances from conventional methodologies to their innovative uses throughout numerous sectors. Composite materials, known for their strength, versatility, and resilience, have seen substantial advances, especially with the incorporation of nanotechnologies and hybrid fiber reinforcements. By means of analyzing exclusive matrix substances, reinforcement sorts, and fabrication techniques, this study highlights the transition from traditional composites to advanced metallic matrix nanocomposites (MMNCS) and fiber-reinforced polymers (FRPS). Special interest is given to the demanding situations associated with manufacturing, together with uniform dispersion of nanoparticles and damage-free machining of fiber composites. Moreover, the paper discusses the environmental impact that specialize in sustainable options like natural fiber reinforcements. Through comprehensive critiques and case studies, this research objectives to offer a holistic information of the cutting-edge state and future potential of composite materials in improving industrial purposes even as addressing environmental concerns.

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Understanding and mitigating delamination in composite materials: A comprehensive review

de Castro Saiki,

Gomes

2024

Mechanics of Advanced Materials and Structures

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On the Use of Machine Learning for Damage Assessment in Composite Structures: A Review

Cited by 4 publications

References 117 publications

A Review of Machine Learning for Progressive Damage Modelling of Fiber-Reinforced Composites

A Review of Machine Learning for Progressive Damage Modelling of Fiber-Reinforced Composites

The Development of Composites Materials: From Conventional to Innovative Uses

Understanding and mitigating delamination in composite materials: A comprehensive review

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