Smart vibro-acoustic control of FGP concrete structures via NC shunt damping and DNN-GA optimization

This research introduces a smart control paradigm for the stochastic vibro-acoustic suppression of functionally graded piezoelectric (FGP) concrete plates, which are developed for the smart concrete structures and systems domain. The proposed method integrates negative capacitance piezoelectric shunt damping (NCPSD), the Carrera Unified Formulation (CUF), and a smart hybrid optimization mechanism comprising deep neural networks and Genetic algorithms (DNN-GA). A detailed multi-layer modeling framework is created through CUF, which efficiently depicts the complex electromechanical responses such as shear deformation, geometric nonlinearity, and spatial grading in the piezoelectric properties. A smart passiveactive damping interface is realized by embedding piezoelectric sensor-actuator pairs connected to a negative capacitance-resistive-inductive (NC-RL) shunt circuit. This setup significantly boosts dynamic adaptability and provides broad bandwidth attenuation. The DNN-GA architecture controls the parameters by tuning them adaptively according to the stochastic excitations and thus navigating through the complex nonlinear response space of the FGP concrete system effectively. The genetic algorithm proceeds rapidly through the zones of the optimal solutions while the deep neural network ensures real-time prediction and adaptation amid the parametric uncertainties. There was a considerable reduction in structural vibration and radiation of acoustic energy particularly in the mid-to-high frequency range, as simulation results indicated. This research supports the possibility of using smart damping solutions for smart concrete structures and systems abroad, especially in the aerospace and automotive industries where the ability to reduce noise and vibrations adaptively is needed the most.