Multi-objective optimization of Spatial Curved Acoustic Metasurface by Genetic Algorithm

Artificial acoustic metasurfaces with good low-frequency sound absorption properties have received extensive attention in the past few years, and different superstructure surfaces have been proposed. Reasonable structural size design is typically necessary for achieving better sound absorption performance in structures, but identifying the ideal size can be a challenging task. this paper suggests an approach to quickly find the appropriate size of the metasurface that meets the given sound absorption coefficient and structural thickness. We first studied the sensitivity of the absorption coefficient to the structural parameters. Based on the sensitivity ranking results, we further analyzed the influence of these structural parameters on the absorption coefficient. Finally, by introducing the Non-Dominated Sorted Genetic Algorithm-II(NSGA-II) in the structural design, the metasurface structure that meet the requirements of a given index can be constructed in the specified frequency range and absorption coefficient, and the structural optimization design of the broadband sound absorption metasurface can be carried out.