Acoustical optimization of mufflers hybridized with spiral perforated tubes using finite element method, Artificial Neural Network, and Genetic Algorithm

Abstract

Because venting noise emitted from high pressure valve often occurred in industry and is huge, the noise abatement of the venting noise to protect human’s hearing health is necessary. In order to depress the high speed noise, a muffler internally equipped with spiral perforated tube is presented. To mitigate this noise, a dissipative muffler with perforated spiral tube installed on the pipeline is proposed. To evaluate the acoustical performance, a finite element method using COMSOL software is adopted. Also, the sensitivity analyses of Transmission Loss (TL) of the proposed muffler with respect to (1) diameter of the spiral and perforated tube (D), (2) pitch of the spiral tube (L), (3) acoustical impedance of the dissipative acoustic material (R), and (4) perforation rate of a perforated tube (σ) has been carried out. For the optimization studies, both Artificial Neural Network (ANN) and Genetic Algorithm (GA) to optimize the muffler parameters L and D are applied. Here, two high target frequencies (2000 and 3500 Hz) to optimize the proposed muffler are exemplified. Consequently, the hybrid design of perforated spiral tube optimized using ANN and GA will mitigate the high pressure valve noise efficiently.