Simulation-based multi-objective muffler optimization using efficient global optimization

• Jobin Puthuparampil ^[1] ; Pierre Sullivan ^[1]
  1. [1] University of Toronto

     University of Toronto

     Canadá

     
• Localización: Noise Control Engineering Journal, ISSN 0736-2501, Vol. 68, Nº. 6, 2020, págs. 441-458
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Noise control of large diesel and natural gas generators is achieved through industrial mufflers. Design of such mufflers relies heavily on general guidelines. However, these guidelines are not suitable for complex mufflers; instead, computer-based optimization provides an effective means of design. Optimization of a plug flow muffler is conducted in this work with a multi-objective (transmission loss and pressure drop) finite element simulation-based optimization using the efficient global optimization (EGO) algorithm. The EGO algorithm is shown to be well suited for computationally expensive muffler optimization, performing vastly better than genetic algorithms, such as the commonly used NSGA-II algorithm. © 2020 Institute of Noise Control Engineering