Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks
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 predi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Lublin University of Technology
2024-02-01
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| Series: | Advances in Sciences and Technology |
| Subjects: | |
| Online Access: | http://www.astrj.com/Prediction-of-Buckling-Behaviour-of-Composite-Plate-Element-Using-Artificial-Neural,177399,0,2.html |
| _version_ | 1797341829483462656 |
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| author | Katarzyna Falkowicz Monika Kulisz |
| author_facet | Katarzyna Falkowicz Monika Kulisz |
| author_sort | Katarzyna Falkowicz |
| collection | DOAJ |
| description | 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 behaviour of composite plates with cut-outs, which can be useful for design optimization and structural monitoring in engineering applications. |
| first_indexed | 2024-03-08T10:24:43Z |
| format | Article |
| id | doaj.art-7990f48b24e341df90e2f60402fd49fa |
| institution | Directory Open Access Journal |
| issn | 2080-4075 2299-8624 |
| language | English |
| last_indexed | 2024-03-08T10:24:43Z |
| publishDate | 2024-02-01 |
| publisher | Lublin University of Technology |
| record_format | Article |
| series | Advances in Sciences and Technology |
| spelling | doaj.art-7990f48b24e341df90e2f60402fd49fa2024-01-27T08:30:32ZengLublin University of TechnologyAdvances in Sciences and Technology2080-40752299-86242024-02-0118123124310.12913/22998624/177399177399Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural NetworksKatarzyna Falkowicz0https://orcid.org/0000-0002-3007-1462Monika Kulisz1Faculty of Mechanical Engineering, Department of Machine Design and Mechatronics, Lublin University of Technology, Nadbystrzycka 36, 20-618 Lublin, PolandFaculty of Management, Department of Organisation of Enterprise, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, PolandThis 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 behaviour of composite plates with cut-outs, which can be useful for design optimization and structural monitoring in engineering applications.http://www.astrj.com/Prediction-of-Buckling-Behaviour-of-Composite-Plate-Element-Using-Artificial-Neural,177399,0,2.htmlartificial neural networknumerical analysisbucklingthin-walled structures |
| spellingShingle | Katarzyna Falkowicz Monika Kulisz Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks Advances in Sciences and Technology artificial neural network numerical analysis buckling thin-walled structures |
| title | Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks |
| title_full | Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks |
| title_fullStr | Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks |
| title_full_unstemmed | Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks |
| title_short | Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks |
| title_sort | prediction of buckling behaviour of composite plate element using artificial neural networks |
| topic | artificial neural network numerical analysis buckling thin-walled structures |
| url | http://www.astrj.com/Prediction-of-Buckling-Behaviour-of-Composite-Plate-Element-Using-Artificial-Neural,177399,0,2.html |
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