Damage characterization of embedded defects in composites using a hybrid thermography, computational, and artificial neural networks approach

This work presents a hybrid thermography, computational, and Artificial Neural Networks (ANN) approach to characterize beneath the surface defects in composites. Computational simulations are created to model thermography experiments carried out on composite plates with controlled damage in the form...

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Detalles Bibliográficos
Autores principales: Al-Athel, Khaled S., Alhasan, Motaz M., Alomari, Ahmed S., Arif, Abul Fazal M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389177/
https://www.ncbi.nlm.nih.gov/pubmed/35991970
http://dx.doi.org/10.1016/j.heliyon.2022.e10063

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389177/
https://www.ncbi.nlm.nih.gov/pubmed/35991970
http://dx.doi.org/10.1016/j.heliyon.2022.e10063

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