Accelerating the Layup Sequences Design of Composite Laminates via Theory-Guided Machine Learning Models

Experimental and numerical investigations are presented for a theory-guided machine learning (ML) model that combines the Hashin failure theory (HFT) and the classical lamination theory (CLT) to optimize and accelerate the design of composite laminates. A finite element simulation with the incorpora...

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Detalles Bibliográficos
Autores principales: Liao, Zhenhao, Qiu, Cheng, Yang, Jun, Yang, Jinglei, Yang, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371008/
https://www.ncbi.nlm.nih.gov/pubmed/35956742
http://dx.doi.org/10.3390/polym14153229

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371008/
https://www.ncbi.nlm.nih.gov/pubmed/35956742
http://dx.doi.org/10.3390/polym14153229

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