Aerodynamic and aeroacoustic optimization for design of a forward-curved blades centrifugal fan

This paper presents a multidisciplinary optimization procedure for enhancing the aerodynamic and aeroacoustic performance of a forward-curved blade centrifugal fan for residential ventilation. Flow analysis in a forward-curved blade centrifugal fan was conducted by solving three-dimensional steady and unsteady Reynolds-averaged Navier–Stokes equations using the shear stress transport turbulence model. On the basis of the aerodynamic sources extracted from the unsteady flow, aeroacoustic analysis was implemented in a finite/infinite element method by solving the variational formulation of Lighthill’s analogy. Experiments were performed to obtain aerodynamic and aeroacoustic measurements for validation of numerical results. The single- and multi-objective optimizations were performed sequentially. The single-objective optimization was carried out to improve the efficiency of the fan using a radial basis neural network surrogate model with four design variables defining the scroll cut-off angle, scroll diffuser expansion angle, diameter ratio of the impeller, and blade exit angle. Multi-objective optimization based on the single-objective optimization result was carried out to simultaneously improve the efficiency and reduce the sound pressure through a hybrid multi-objective evolutionary algorithm coupled with a response surface approximation surrogate model with two design variables defining the scroll cut-off radius and distance. These objective functions were accessed numerically through three-dimensional aerodynamic and aeroacoustic analyses at the design points sampled by Latin hypercube sampling in the design space. Arbitrary selected optimum designs in the Pareto-optimal solutions yielded significant increases in efficiency and decreases in the sound pressure level compared to the reference design.