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中文摘要：
为全面提升对转压气机气动性能,以某双级对转压气机为研究对象,基于人工神经网络与遗传算法,针对转子2叶片在整机环境下进行全工况优化设计,并对优化前后几何形状、总体性能及流场结构进行了对比分析.结果表明：优化后对转压气机全工况范围内等熵效率及压比均得到提升,同时流量范围有所增大.在设计点整机等熵效率提高0.3%,近失速点整机等熵效率提高1.5%,喘振裕度上升了6.37%,稳定工作范围得到显著扩大.优化后转子1全工况范围内等熵效率和压比特性变化不大,而转子2全工况范围内等熵效率和压比均有较大提高,其中在设计点转子2等熵效率上升1%,近失速点转子2等熵效率上升2.5%;在近失速点,优化后转子1、转子2、出口导叶（OGV）尖部流场显著改善.
英文摘要：
In order to improve aerodynamic performance of the counter-rotating com- pressor 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 per formance and flow field were compared and analyzed. Results show that： after the optimiza- tion, 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 optimiza- tion, 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. Al- so, the flow fields of Rotor 1, Rotor 2 and outlet guide vane （OGV） at the tip are improved remarkably near the stall point.
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