In this study, the unique reverse-flow around the inlet nozzle of a squirrel-cage fan was numerically studied by computational fluid dynamics (CFD), and a non-axisymmetric D-type inlet nozzle was proposed to inhibit it. It is shown that serious back flow develops at the volute tongue when the fan operates at a low flow coefficient that is lower than the best efficiency point. The airflow passing the blade passages in reverse further crosses the impeller, mixing the clearance leakage airflow, and finally blows into the intake chamber near the circumferential position of ${150}^{\circ }$. By installing the inlet nozzle along this direction, D-type inlet nozzle schemes with different blockage extent were calculated by CFD. The scheme with a cut distance of 70% of its exit-section radius was chosen as the best design by comprehensively comparing the back flow ratio and fan performance of different working conditions. CFD results illustrated that reverse blowing at the fan entrance was significantly constrained by this D-type inlet nozzle, and the vortex in the inlet chamber correspondingly disappeared. Experimental data illustrated that the new nozzle increased the fan pressure rise under low-flow conditions by about 6% and barely reduced performance at other working points.

In this study, a dual-arc profile parameterized by four geometric variables was designed to replace the original single-arc profile of a squirrel-cage fan used in a range hood, in order to improve the efficiency of the entire machine and the fan pressure. A modified Non-dominated Sorting Genetic algorithm coupled with a three-dimensional Reynolds-averaged Navier–Stokes computation is applied to search the optimum blade shape. Moreover, a relatively coarse but proven reliable grid model is employed to accelerate the optimization process, and a dynamic crowding distance is applied to improve the broad diversity of the Pareto front. The optimization results show that the optimal dual-arc blades are formed by a leading arc with a relatively smaller curvature and a trailing arc with a larger curvature, and the shape of the leading arc dominates the aerodynamic performance of the dual-arc blade. The blade schemes at two end of the Pareto front have increased the fan pressure and efficiency at the optimization point by 5.3% and 1.5%, respectively, but also result in a decline in another performance indicator. The best compromised solution in the middle of the Pareto front has improved the pressure by 2.6% without reducing the efficiency in the numerical calculation. Compared with the single-arc blade with the same inlet and outlet angle, the dual-arc blade has a higher fan pressure, but at the same time, the efficiency is negatively affected. Finally, the new impeller with optimized dual-arc blades is manufactured and tested, and the experimental results show an increment exceeds 2% in pressure and an unexpected slightly improvement in fan efficiency.

The flow pattern in the volute of a squirrel cage fan is complicated and non-axisymmetric. In this article, the original volute profile of a squirrel cage fan was cut to control and reshape this non-axisymmetric flow structure. An experimental study was conducted to investigate the effects of the cut volute profile on the fan aerodynamic and acoustic performance. The results showed that cutting the volute profile with a relative cut position of 90° and a secondary clearance of 0.02 D₂ could enhance the fan total pressure at the volume flow rate of 0.4 Q_BEP by about 7% without affecting the noise level. High-precision steady computational fluid dynamics simulation was also carried out to reveal the flow mechanism of the performance improvement. The results indicated that cut volute profile caused an impeller-across flow structure in the vicinity of the second clearance and re-organized the circumference distribution of the impeller flow status. Both the impeller working capability and the overall flow losses of the cut fan increased compared to the original one but the increment of the former was greater. This explains why fan pressure improved under low-flow conditions.

The performance of low-pressure axial flow fans is directly affected by the three-dimensional bending and twisting of the blades. A new blade design method is adopted in this work, where the radial distribution of blade angle and blade bending angle is composed of standard-form rational quadratic Bézier curves. Dendrite Net is then trained to predict the pneumatic performance of the fan. A non dominated sorting genetic algorithm is employed to solve the global optimization problem of the total pressure coefficient and efficiency. The simulation results show that the optimal blade load distribution along the radial direction becomes uniform, and the suction surface separation vortex and passage vortex are restrained. On the other hand, the tip leakage vortex is enhanced and moves toward the blade leading edge. According to the experimental results, the maximum efficiency increases by 5.44%, and the maximum total pressure coefficient increases by 2.47% after optimization.