Multi-Objective Collaborative Optimization of Stiffness and Damping Performance of Acoustic Black Hole Plate

Abstract

This paper uses embedded Acoustic Black Hole (ABH) on the wallboard for structure lightening and improving the performance in broadband vibration reduction. The distribution and size of multiple ABHs affect the generalized static stiffness (GSS) and the upper limit of the structure's maximum kinetic energy (ULMKE) in practical applications, which express the ability to resist static load and vibration reduction performance, respectively. In this research, the structure's GSS and ULMKE are considered optimization objectives due to the trade-off between them. The method based on the Pareto optimal solution is adopted to optimize the layout and the radii of the ABHs. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is used as the multi-objective optimization algorithm. Two 2D-ABHs embedded in a plate are optimized as numerical examples. The optimization generated several groups of Pareto optimal solutions, providing more feasible solutions for different applications faster. The verification further proved the necessity and the effectiveness of multi-objective optimization.