Artificial Neural Network (ANN) Validation Research: Free Vibration Analysis of Functionally Graded Beam via Higher-Order Shear Deformation Theory and Artificial Neural Network Method

被引:0
|
作者
Celik, Murat [1 ]
Gundogdu, Emircan [2 ]
Ozdilek, Emin Emre [1 ]
Demirkan, Erol [1 ]
Artan, Reha [1 ]
机构
[1] Istanbul Tech Univ, Dept Civil Engn, TR-34469 Istanbul, Turkiye
[2] Istanbul Tech Univ, Dept Comp Engn, TR-34469 Istanbul, Turkiye
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 01期
关键词
functionally graded material; composite beam; artificial neural network; free vibration; PLATES;
D O I
10.3390/app14010217
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Presented herein is the free vibration analysis of functionally graded beams (FGMs) via higher-order shear deformation theory and an artificial neural network method (ANN). The transverse displacement (w) is expressed as bending (wb) and shear (ws) components to define the deformation of the beam. The higher-order variation of the transverse shear strains is accounted for through the thickness direction of the FGM beam, and satisfies boundary conditions. The governing equations are derived with the help of Hamilton's principle. Non-dimensional frequencies are obtained using Navier's solution. To validate and enrich the proposed research, an artificial neural network method (ANN) was developed in order to predict the dimensionless frequencies. Material properties and previous studies were used to generate the ANN dataset. The obtained frequency values from the analytical solution and ANN method were compared and discussed with respect to the mean error. In conclusion, the solutions were demonstrated for various deformation theories, and all of the results were thereupon tabularized and visualized using 2D and 3D plots.
引用
收藏
页数:15
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