AI Based Free Vibration Analysis of Sandwich Shells with Viscoelastic Core

Abstract

This study investigates the dynamic response of a three-layer sandwich shell with isotropic face layers and a viscoelastic core. The investigation employs both experimental modal analysis and numerical analysis to determine the natural frequencies and modal loss factors of the sandwich shell under various boundary conditions. The experimental free vibration test is conducted employing the impact hammer method, while the numerical analysis is performed through finite element modelling. To enhance the predictive capabilities, artificial neural network (ANN)-based models are developed and trained using the numerical simulation data. The ANN models effectively learn the complex relationships between the structural parameters and the dynamic characteristics, enabling quick and reliable predictions of free vibration and damping properties. The integration of AI-driven predictive techniques with conventional experimental and numerical methods highlights the potential of machine learning. The study’s findings underscore the effectiveness of the proposed approach, offering a promising framework for structural health monitoring, optimization of sandwich structures, and the design of advanced materials.