Acoustic optimization for centrifugal fans

The aim of this study is to perform a multi-objective optimization in order to re¬duce the noise level of a centrifugal fan in early design stages. The main goal is to minimize the ?ow-induced noise while providing the required pressure rise at the operating ?ow rate. The design procedure begins with a baseline fan. An optimi¬zation surface around the baseline design is formed by using the design of experi¬ments method. Accordingly, geometric parameter sets and the corresponding CAD models are generated. Flow through these fans is simulated via Reynolds averaged Navier-Stokes equations. Flow data are evaluated to predict the noise level and the fan performance. Neural network method is employed to determine the family of optimum points. Two of the Pareto designs are manufactured with rapid prototyping in order to validate the numerical optimization procedure via aerodynamic and aeroacoustic experiments. Experiments show that both designs satisfy optimization goals.