Optimization design of a two-stage counter-rotating compressor under overall working conditions

In order to improve aerodynamic performance of the counter-rotating compressor in an all-round way, overall working conditions optimization design was carried out on the Rotor 2 of a two-stage counter-rotating compressor in multistage environment based on artificial neural network and genetic algorithm. The changes of geometry, overall performance and flow field were compared and analyzed. Results show that: after the optimization, the overall isentropic efficiency and pressure ratio of the counter-rotating compressor are both improved, meanwhile the range of mass flow is widened. The isentropic efficiency of the counter-rotating compressor increases by 0.3% on the design point, increases by 1.5% near the stall point, and the surge margin increases by 6.37%. After the optimization, the overall isentropic efficiency and pressure ratio of the Rotor 1 are almost unchanged, but those of Rotor 2 are raised much. The isentropic efficiency of Rotor 2 improves by 1% on the design point, and the isentropic efficiency is improved by 2.5% near the stall point. Also, the flow fields of Rotor 1, Rotor 2 and outlet guide vane (OGV) at the tip are improved remarkably near the stall point.