Abstract
Background
Circular and parabolic curved beams are the essential elements of many engineering structures possessing diversified applications. Therefore, the comprehensive study of their dynamic behavior is very important.
Purpose
The present research focuses on developing an Adaptive neuro-fuzzy inference system (ANFIS) model and deriving empirical equations for estimating the natural frequencies of circular and parabolic beams.
Methodology
For developing ANFIS models, 81 numbers of datasets each of circular and parabolic beams are procured from the numerical investigation carried out using finite element modeling software ANSYS. Experimental validation of obtained numerical results is conducted using FFT (Fast Fourier transform) spectrum analyzer.
Results and Conclusion
The input parameters considered for developing the ANFIS model for circular beams are cross-section area, support conditions, curvature angle, and mode number. Similarly, input parameters for parabolic beams are support conditions, cross-sectional area, rise to span length ratio, and mode number. The performance of the input parameter is evaluated using different statistical indices such as root mean square error (RMSE), coefficient of determination (\({R}^{2}\) ), and mean absolute error (MAE). Sensitivity analysis is carried out to identify the most influential input parameter in determining the natural frequency of curved beams. The performance evaluation and comparison of the ANFIS model with the numerical model assert that ANFIS can efficiently predict natural frequency.
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Mohanty, N., Sasmal, S.K., Mishra, U.K. et al. Experimental and Computational Analysis of Free In-Plane Vibration of Curved Beams. J. Vib. Eng. Technol. 11, 1777–1796 (2023). https://doi.org/10.1007/s42417-022-00670-1
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DOI: https://doi.org/10.1007/s42417-022-00670-1