Temperature Variation Effects on the Vibrational Behaviour of Trapezoidal Plate: An ANN – Based Prediction Technique

Abstract

This research scrutinized the effect of temperature variation on the vibrational analysis of a non – homogeneous trapezoidal – shaped plate with the consideration of dual – exponential thickness alteration. This examination evaluates a structural plate governed by C–C–C–S edge constraints, where three boundaries are rigidly supported and the remaining edge is supported in a simple manner. The study assesses the consequence of thermal variation on the primary two vibration-related modes. A governing vibrational formulation is constructed by applying Rayleigh–Ritz approach. Maple software is employed to measure frequency characteristics across various temperature scenarios. To complement the mathematical formulation, an Artificial Neural Network (ANN) model is constructed to predict the primary and secondary vibrational mode frequency values depending on the parameter of temperature variation. The numerical results acquired through the Rayleigh–Ritz scheme function as the baseline dataset for training, validation, and assessment the artificial neural network model.