A Many-Objective Joint Parallel Simulation Method for Acoustic Optimization Design of Sound-Absorbing Structures

Abstract

This paper establishes a many-objective MATLAB with a COMSOL joint parallel simulation optimization method in order to solve the current situation of low efficiency, single objective, and poor effect in acoustic optimization design research for a sound-absorbing structure. Our proposed method combines the means for population partitioning, monitoring, and adaptive normalization, within the framework of the NSGA-III algorithm, which takes the hyperplane deployment scheme into account in its entirety. Compared to the traditional genetic algorithm toolbox of the joint COMSOL optimization scheme, it is shown that the joint parallel simulation optimization method that is constructed in this paper achieves a higher optimization efficiency and a better experimental performance, thereby aiding in the identification of the optimal solution to multiple objectives. The optimization efficiency can increase linearly as the number of available cores on the computer increases. This method is then used to construct a parallel, low-frequency, broadband, highly-sound-absorbing structure. Without any constraints on the optimization objective, the diversity of the optimization results is evident within the parameter optimization range of this paper. The optimization results are stable and substantial, with constrained optimization objectives that have some reference value. In addition, the proposed method can solve acoustic vibration optimization problems and can be applied to other finite element optimization problems.