SHAPE OPTIMIZATION OF MULTI-CHAMBER MUFFLERS WITH PLUG-INLET TUBE ON A VENTING PROCESS BY GENETIC ALGORITHMS

Research on new techniques of single-chamber plug-inlet mufflers has been addressed. However, research work on shape optimization of multi-chamber plug-inlet mufflers along with work on the maximal back pressure has been neglected. Therefore, a numerical case for eliminating a broadband steam blow-off noise using multi-chamber plug-inlet mufflers in conjunction with genetic algorithm (GA) as well as numerical decoupling technique under space-constrained pressure drop is introduced in this paper. To verify the liability of GA optimization, optimal noise abatements for various pure tones on a one-chamber plug-inlet muffler are exemplified. Also, the accuracy of the mathematical model has to be checked by experimental data. Results indicate that the maximal sound transmission losses are precisely located at the desired target tones. Consequently, both the pressure drop and the acoustical performance will be increased when the diameters (at inlet tubes and perforated holes), the perforated ratio, and the length of perforated tube decrease.