چكيده به لاتين
In recent decades, with the rapid growth of various industries such as aerospace and automotive, noise sources have increased significantly, causing many problems for human health and the natural cycle of the ecosystem. Therefore, new methods should be developed to reduce the noise level. Membrane-type acoustic metamaterials, due to their good performance in reducing low-frequency noise, lightness, and tunability of the working frequency, have attracted the attention of researchers. These metamaterials, due to the provision of local resonance mechanism, absorb low-frequency sounds well in a wide frequency range. In this thesis, a membrane-type acoustic metamaterial with an asymmetric geometric structure based on the local resonance mechanism and negative effective parameters is designed and optimized using a genetic algorithm to maximize the sound transmission loss and the working frequency range. Using the finite element method in COMSOL software, the initial model of the metamaterial, which has different masses attached to it, is designed and four geometric parameters of the structure are selected for the optimization problem. These parameters include changing the geometric dimensions of the bodies (length and width) and displacing their position on the membrane structure (linear and angular). Then, the developed genetic algorithm is coupled to COMSOL software through COMSOL Livelink with MATLAB and the optimization results are obtained under the Acoustic-solid interaction module of COMSOL software. The results showed that the genetic algorithm converged after 64 iterations and the sound transmission loss and working frequency increased to 21.7 Db and 92%, respectively. The physical mechanism of the results was justified by examining the vibration modes of the structure, the negative effective parameters, such as effective mass and stiffness, and the average displacement of the membrane surface. Also, the effect of each of the selected parameters for the optimization problem was investigated under sensitivity analysis, which showed that the geometric parameters of the bodies have more effect on the average sound transmission loss than the positional parameters. Finally, the optimized structures were put together, made a crystal lattice, and then placed inside the exhaust muffler. Acoustic and fluid results showed that, compared to the empty muffler, not only the acoustic performance of the MAM-based muffler improved, but also it did not prevent the fluid movement in the muffler. These results shed the light on the applicability of such MAMs in real world applications and paved the way for future research in designing MAM.
