Teaching-learning-based optimization of an ultra-broadband parallel sound absorber

Abstract

The average sound-absorption coefficient of an ultra-broadband parallel sound absorber, between 0 and 2000 Hz, is optimized in certain conditions. This is accomplished using a teaching–learning-based optimization algorithm, where the geometric parameters are used as optimization variables. The optimized ultra-broadband parallel sound absorber has an average sound-absorption coefficient of 0.9255. The surface impedance of its structure is almost perfectly matched with the surrounding air – thanks to the optimized lengths of both the lateral and micro-perforated plates. The effective-medium model, the transfer-matrix method, and the finite-element method are applied and show consistent results. The acoustic-impedance tube measurements confirm that the optimized ultra-broadband parallel sound absorber shows high sound-absorption from 200 to 1715 Hz. The investigated passive acoustic design opens new possibilities for new absorber types in the future.