双级对转压气机全工况优化设计

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.

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.