The multi-blade centrifugal fan is commonly used in modern building ventilation and air-conditioning system. However, it does not readily satisfy the increasing demand for energy saving, high efficiency or noise reduction. Its performance is inherently limited by the geometrical structure of single circular arc blades. Q35-type multi-blade centrifugal fan studied as an example by combining the disturbance CST function to parameterize the blades. The optimization parameter change range is confirmed, and test samples are extracted before establishing an RBF proxy model. The NSGA-II algorithm is incorporated, and multi-objective optimization is performed with flow rate and total pressure efficiency as optimization goals. The results show that the fan performance is effectively improved. At the design working point, the air volume of the multi-blade centrifugal fan increases by 1.4 m³/min; at the same time, the total pressure efficiency increases by 3.1%, and the noise is reduced by 1.12 dB, applying the proposed design. The obtained higher fan efficiency can effectively improve performance of the whole ventilation and air-conditioning system. This novel optimization method also has relatively few parameters, which makes it potentially valuable for designing multi-wing centrifugal and other types of fans, providing a new idea for energy saving and emission reduction design of fan.

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Nuclear grade axial flow fans are widely used in nuclear power plants for ventilation and heat dissipation and have the advantages of high efficiency and high flow rates. A nuclear grade axial flow fan with OGVs (outlet guide vanes) can recover the kinetic energy of the dynamic impeller outlet winding to increase the ventilator pressure, thus improving the ventilator efficiency; therefore, the OGVs play an essential role in the performance of the axial flow fan. Based on accurate numerical simulations, an MRGP approximation model was developed to analyse the factors affecting the OGVs duct and optimise the guide vane structure, combined with the Sobol method for sensitivity analysis. The experiments and numerical simulations show that the total pressure of the optimised model increases by 154 Pa, and the noise decreases by 4.1 dB. The multi-objective optimisation method using the parametric approach and combining it with the MRGP model is highly reliable. It provides a key design direction for optimising nuclear grade axial flow fans.

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