Kallannavar, Vinayak and Kattimani, Subhaschandra and Soudagar, Manzoore Elahi M. and Mujtaba, M. A. and Alshahrani, Saad and Imran, Muhammad (2021) Neural network-based prediction model to investigate the influence of temperature and moisture on vibration characteristics of skew laminated composite sandwich plates. Materials, 14 (12). ISSN 1996-1944, DOI https://doi.org/10.3390/ma14123170.
Full text not available from this repository.Abstract
The present study deals with the development of a prediction model to investigate the impact of temperature and moisture on the vibration response of a skew laminated composite sandwich (LCS) plate using the artificial neural network (ANN) technique. Firstly, a finite element model is generated to incorporate the hygro-elastic and thermo-elastic characteristics of the LCS plate using first-order shear deformation theory (FSDT). Graphite-epoxy composite laminates are used as the face sheets, and DYAD606 viscoelastic material is used as the core material. Non-linear strain-displacement relations are used to generate the initial stiffness matrix in order to represent the stiffness generated from the uniformly varying temperature and moisture concentrations. The mechanical stiffness matrix is derived using linear strain-displacement associations. Then the results obtained from the numerical model are used to train the ANN. About 11,520 data points were collected from the numerical analysis and were used to train the network using the Levenberg-Marquardt algorithm. The developed ANN model is used to study the influence of various process parameters on the frequency response of the system, and the outcomes are compared with the results obtained from the numerical model. Several numerical examples are presented and conferred to comprehend the influence of temperature and moisture on the LCS plates.
| Item Type: | Article |
|---|---|
| Funders: | Deanship of Scientific Research at King Khalid University, Saudi Arabia [RGP.1/132/42], Science and Engineering Research Board (DST-SERB) [EEQ/2017/000744] |
| Uncontrolled Keywords: | Artificial neural network; Finite element analysis; Shear deformation theory; Skew angle; Sandwich plates; Effect of temperature and moisture |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Faculty of Engineering > Department of Mechanical Engineering |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 04 Aug 2022 02:02 |
| Last Modified: | 04 Aug 2022 02:02 |
| URI: | http://eprints.um.edu.my/id/eprint/28400 |
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