Design optimization of a supersonic through-flow fan rotor based on the blade profiles

In this study, the authors propose an optimization process to design the baseline rotor of a supersonic through-flow fan (STFF) at an inlet Mach number of 2.0 based on Genetic Algorithm. Unlike the improvement in performance brought about by the pre-compression of conventional supersonic profiles in the presence of axial pressure flow, pre-compression did not help improve the performance of the rotor of the STFF. The efficiency of elements of the blade at spanwise heights of 10%, 50%, and 90% increased by 2.47%, 1.95%, and 2.49%, respectively. The performance of the rotor of the STFF that was reconstructed by stacking the optimized elements of the blade was improved at the design point as well as in off-design conditions by using three-dimensional computational fluid dynamics (CFD) simulations. The performance of the blade also improved considerably, with increases of by 2.46% and 9.59% in its isentropic efficiency and the overall pressure ratio, respectively.