Shape optimization of multi-chamber mufflers with plug-inlet tube on a venting process by genetic algorithms

Recently, research on new techniques of single-chamber plug-inlet mufflers has been amply addressed. However, research work on shape optimization of multi-chamber plug-inlet mufflers along with work on maximal back pressure has been sorely neglected. Therefore, a numerical case for eliminating broadband steam blow-off noise using multi-chamber plug-inlet mufflers in conjunction with a genetic algorithm (GA) as well as a numerical decoupling technique, all within a space-constrained pressure drop, is introduced in this paper. To verify the reliability of the GA optimization, optimal noise abatements for various pure tones on a one-chamber plug-inlet muffler are examined. Of course, the accuracy of the mathematical model must be supported by experimental data. Subsequently, optimal results then indicate that the maximal sound transmission losses are indeed located at the desired target tones. Consequently, both pressure drop and acoustical performance will increase when the diameters (at inlet tubes and perforated holes), the perforated ratio, and the length of perforated tubes are decreased.