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 cutoff 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 cutoff radius and distance. These objective functions were accessed numerically through threedimensional 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.

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In the present work, the fluid flow characteristics of a mixed-flow pump have beenwere investigated numerically using threedimensional Reynolds-averaged Navier-Stokes equations. The shear stress transport turbulence model and hexahedral grid system were used to analyze the flow in the mixed-flow pump. The efficiency of the mixed-flow pump was evaluated using the variation of two geometric variables related to the inlet angle of the diffuser vane. The design optimization of the mixed-flow pump was performed to maximize the its efficiency at the prescribed specific speed using a surrogate model. Latin hypercube sampling was used to determine the training points for the design of the experiment, and the surrogate model was constructed using the objective function values at the training points. The results show that the efficiency of the mixed-flow pump at the prescribed specific speed is improved considerably by the design optimization.

Multi-objective optimization of a centrifugal fan with additionally installed splitter blades was performed to simultaneously maximize the efficiency and pressure rise using three-dimensional Reynolds-averaged Navier-Stokes equations and hybrid multi-objective evolutionary algorithm. Two design variables defining the location of splitter, and the height ratio between inlet and outlet of impeller were selected for the optimization. In addition, the aerodynamic characteristics of the centrifugal fan were investigated with the variation of design variables in the design space. Latin hypercube sampling was used to select the training points, and response surface approximation models were constructed as surrogate models of the objective functions. With the optimization, both the efficiency and pressure rise of the centrifugal fan with splitter blades were improved considerably compared to the reference model.