Shape optimization on constrained linearly expanded tubes by using genetic algorithm

One of the most important practical considerations in muffler design is the constrain problems in a confined place. In addition, to release the pressure drop in a muffler system, a new silencer of linearly expanded tube is proposed and investigated in this paper. The genetic algorithm (GA), a stochastic algorithm, is used as an optimizer by mimicking the genetic drift and Darwinian strife for survival. To approach this study effectively, the linearly inclined tube is divided into several segments of straight tube with different diameters. Four-pole transfer matrix is then in use, accordingly. Not only the theoretical derivation in sound transmission loss (STL) but also the GA searching technique is discussed. Additionally, a numerical case on the expanded tube is introduced. To achieve the best optimization in terms of STL of a muffler, the GA parameters are on trial in various values. Results show that when the divided elements of the tube are more than sixteen segments, the modeled segmental tube is similar to the linearly expanded tube. In addition, the STL in muffler becomes to be stable.