Failure Analysis and Prediction of Hybrid Composite Laminate under Biaxial Tension using Artificial Neural Network
Hybrid composite laminates such as Boron/Epoxy or Glass/Epoxy show complex failure behaviour when subjected to biaxial tension on which it is difficult to accurately predict the failure load. In order to tackle this problem, we aim to develop an Artificial Neural Network model that can precisely for...
الحاوية / القاعدة: | 2024 IEEE 22nd Student Conference on Research and Development, SCOReD 2024 |
---|---|
المؤلف الرئيسي: | 2-s2.0-85219586558 |
التنسيق: | Conference paper |
اللغة: | English |
منشور في: |
Institute of Electrical and Electronics Engineers Inc.
2024
|
الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85219586558&doi=10.1109%2fSCOReD64708.2024.10872670&partnerID=40&md5=8b049dc2d52d44e695f6eb9ab8bb85df |
مواد مشابهة
-
Natural Frequencies Prediction of Hybrid Composite Laminate based on Finite Element Simulation and Artificial Neural Network
بواسطة: 2-s2.0-85219506859
منشور في: (2024) -
Predicting fraudulent financial reporting using artificial neural network
بواسطة: 2-s2.0-85019490600
منشور في: (2017) -
Artificial Neural Network-Salp-Swarm Algorithm for Stock Price Prediction
بواسطة: Mustaffa Z.; Sulaiman M.H.; Aziz A.A.
منشور في: (2024) -
Prediction of Electromagnetic Properties Using Artificial Neural Networks for Oil Recovery Factors
بواسطة: 2-s2.0-85152886016
منشور في: (2023) -
Artificial neural network modelling and flood water level prediction using extended Kalman filter
بواسطة: 2-s2.0-84875980418
منشور في: (2012)