Multi-gradient acoustic black hole metamaterial for near-perfect sound Attenuation: Theory, simulation and experiments

Abstract

A multi-gradient acoustic black hole metamaterial module (MABHM) based on a genetic algorithm-neural network (NN-GA) is optimally designed for near-perfect sound attenuation of sub-wavelength metamaterial structures. Simulation results show that the absorption coefficient of the MABHM is up to more than 0.9 in the range of 300 Hz-20 kHz, and the MABHM has a good absorption effect for sound waves with different incident angles. The complex acoustic impedance of the MABHM has a phase loop approximating near the (1,0) coordinates. It is proved that the impedance matching effect is the key to realizing near-perfect sound absorption. The sound transmission loss curves of MABHM with different perforation ratios are the same, and the sound insulation at frequencies above 200 Hz reaches more than 35.0 dB. The experimental results of sound absorption coefficient and sound transmission loss are consistent with the simulation results. MABHM has the advantages of low-frequency broadband sound absorption and insulation, which can be used to realize nearly perfect noise reduction.