Inverse design of multi-band acoustic topology insulator based on deep learning

Abstract

The reverse design method of acoustic structure based on a deep learning algorithm has been developed as an important means of metamaterial design. In this paper, a multi-band acoustic topological insulator is designed, and the improved competitive search algorithm Long Short-Term Memory (LSTM) algorithm model is used to predict its potential optimal parameter combination to assist the on-demand design of the working frequency band of the multi-band acoustic topology insulator. Finally, the numerical simulation model is established using the optimized structural parameters, and the topologically protected boundary state is studied, which verifies the effectiveness of the method. The research results provide a reference for the on-demand design of multi-band antennas, sound absorption, sound insulation, and other acoustic communication functional devices.