A framework for designing a modular muffler system by global optimization

Abstract: When creating a muffler to be installed on a noise generating machine, the design parameters as well as the placements of sound attenuating elements has to be optimized in order to minimize the sound coming out of the equipage. This is exemplified in a small project task for students of a basic course in optimization at KTH. The task is however flawed, since both the way in which the optimization problem is formed is overly simplistic and the algorithm used to solve the problem, fmincon, does not cope well with the mathematical complexity of the model, meaning it gets stuck in a local optimum that is not a global optimum. This thesis is about investigating how to solve both of these problems. The model is modified to combine several frequencies and adjusting them to the sensitivity to different frequencies in the human ear. By doing this, the objective is changed from the previous way of maximizing Dynamic Insertion Loss Dilfor a specific frequency to minimize the total perceived sound level LA.  The model is based on the modular design of TMM from four-pole theory. This divides the muffler into separate parts, with the sound attenuating elements being mathematically defined only by what T matrix it has. The element types to choose from are the Expansion Chamber, the Quarter Wave Resonator and the Helmholtz Resonator. The global optimization methods to choose from are Global Search, MultiStart, Genetic Algorithm, Pattern Search and Simulated Annealing. By combining the different types of sound attenuating elements in every way and solving each case with every global optimization method, the best combination to implement to the model is chosen. The choice is two Quarter Wave Resonators being solved by MultiStart, which provides satisfactory results. Further analysis is done to ensure the robustness of chosen implementation, which does not reveal any significant flaws. The purpose of this thesis is fulfilled.