Application of Genetic Algorithm to the Shape Optimization of a Constrained Double-Chamber Muffler with Extended Tubes

As the compact design of a muffler system within a constrained environment of a existing machine room becomes obligatory, it also becomes essential to maximize the acoustic performance of mufflers under space constraints. In this paper, the shape optimization of a double-chamber muffler with an extended tube is presented. The main characteristic of the solution methodology is the use of genetic algorithm (GA) as the optimizer. In the paper, the acoustic performance of sound transmission loss (STL) derived by transfer matrix is conjugated with the techniques of GA searching. A numerical case of noise elimination in full band noise is also exemplified and fully discussed in this paper. Before GA operation, the presented theory of a single-chamber muffler with extended tubes is simulated and compared with Wang and Hsieh's experimental data for the purpose of accuracy check in the mathematical model. Thereafter, a simple optimal program in dealing with pure tone noise of 500 Hz has been pre-run to verify the correctness of the genetic algorithm before the design in full band noise will be performed. Results reflect the accuracy of the mathematical model and the correctness of the GA method. The optimal design of STL proposed in this study provides a quick and correct approach.

並列關鍵字

shape optimization ； double-chamber muffler with extended tubes ； transfer matrix method ； space constraints ； genetic algorithm

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