Capability of energy harvesting in cantilever piezoelectric-actuated arch structures via highly accurate semi numerical method

Abstract

The use of nanoscale arch structures in vibration detection has become popular due to their ability to capture resonance in two independent directions. This study investigates the vibration behavior of a small-scale cantilever curved beam structure made of a functionally graded carbon nanotube reinforced nanocomposite core and piezoelectric surface layers on a viscoelastic substrate. The piezoelectric layers convert motion into electrical signals, allowing for the harvesting of high-frequency motions in a delicate manner. Various theories, including the first-order shear deformation theory, strain gradient theory, and nonlocal theory, are used to capture the mechanical properties of the FG nanocomposite core at both nano- and micro-scales. The equations of motion and natural boundary conditions are derived using Hamilton’s principle and solved using Akbari-Ganji’s method. An artificial intelligence method is also presented to simplify the solution procedure and calculate numerical results based on important parameters in the vibrational behavior analysis. The study demonstrates the significance of viscoelastic properties of the substrate and the volume fraction of CNT in composite core in the frequency analysis of the arch structure, as shown by the results of both the numerical and AI methods.