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Multipoint and Multiobjective Optimization of a Centrifugal Compressor Impeller Based on Genetic Algorithm

机译:基于遗传算法的离心压缩机叶轮多点多目标优化

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The design of high efficiency, high pressure ratio, andwide flowrange centrifugal impellers is a challenging task. Thepaper describes the application of a multiobjective, multipoint optimization methodology to the redesign of a transonic compressor impeller for this purpose. The aerodynamic optimization method integrates an improved nondominated sorting genetic algorithm II (NSGAII), blade geometry parameterization based on NURBS, a 3D RANS solver, a self-organization map (SOM) based data mining technique, and a time series based surge detection method. The optimization results indicate a considerable improvement to the total pressure ratio and isentropic efficiency of the compressor over the whole design speed line and by 5.3% and 1.9% at design point, respectively. Meanwhile, surge margin and choke mass flow increase by 6.8% and 1.4%, respectively. The mechanism behind the performance improvement is further extracted by combining the geometry changes with detailed flow analysis.
机译:高效,高压力比和宽流量范围的离心叶轮的设计是一项艰巨的任务。本文介绍了多目标,多点优化方法在为此目的设计跨音速压缩机叶轮的过程中的应用。空气动力学优化方法集成了改进的非支配排序遗传算法II(NSGAII),基于NURBS的叶片几何参数化,3D RANS求解器,基于自组织图(SOM)的数据挖掘技术以及基于时间序列的喘振检测方法。优化结果表明,在整个设计速度线上,压缩机的总压比和等熵效率都有了显着提高,在设计点分别提高了5.3%和1.9%。同时,喘振裕度和节流质量流量分别增加了6.8%和1.4%。通过将几何形状变化与详细的流量分析相结合,进一步提取了性能改进背后的机制。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第9期|6263274.1-6263274.18|共18页
  • 作者单位

    Tianjin Univ, Dept Mech, Tianjin 300072, Peoples R China;

    Tianjin Univ, Dept Mech, Tianjin 300072, Peoples R China;

    Kingston Univ London, Sch Mech & Aerosp Engn, London SW15 3DW, England;

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