Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks
Artykuł w czasopiśmie
MNiSW
100
Lista 2024
Status: | |
Autorzy: | Falkowicz Katarzyna, Kulisz Monika |
Dyscypliny: | |
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Rok wydania: | 2024 |
Wersja dokumentu: | Drukowana | Elektroniczna |
Język: | angielski |
Numer czasopisma: | 1 |
Wolumen/Tom: | 18 |
Strony: | 231 - 243 |
Impact Factor: | 1,0 |
Web of Science® Times Cited: | 6 |
Scopus® Cytowania: | 9 |
Bazy: | Web of Science | Scopus |
Efekt badań statutowych | NIE |
Finansowanie: | The grant was financed in the framework of the pro-quality program of Lublin University of Technology “Grants for grants” (6/GnG/2023) |
Materiał konferencyjny: | NIE |
Publikacja OA: | TAK |
Licencja: | |
Sposób udostępnienia: | Witryna wydawcy |
Wersja tekstu: | Ostateczna wersja opublikowana |
Czas opublikowania: | W momencie opublikowania |
Data opublikowania w OA: | 15 stycznia 2024 |
Abstrakty: | angielski |
This article presents the use of artificial neural networks (ANNs) to analysis of the composite plate elements with cut-outs which can work as a spring element. The analysis were based on results from numerical approach. ANNs models have been developed utilizing the obtained numerical data to predict the composite plate’s flexural- torsional form of buckling as natural form for different cut-outs and angels configurations. The ANNs models were trained and tested using a large dataset, and their accuracy is evaluated using various statistical measures. The developed ANNs models demonstrated high accuracy in predicting the critical force and buckling form of thin-walled plates with different cut-out and fiber angels configurations under compression. The combination of numerical analyses with ANNs models provides a practical and efficient solution for evaluating the stability be- haviour of composite plates with cut-outs, which can be useful for design optimization and structural monitoring in engineering applications. |