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Statistical evaluation of performance impact of flow variations for a transonic compressor rotor blade

机译:跨音速压缩机转子叶片的流动变化性能影响的统计评估

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The effects of flow variations to the aerodynamic performance of turbomachinery blades are considerable in the real world. Uncertainty quantification of aerodynamic performance is useful for evaluating the mean performance change, robust design, etc. The paper studies the performance impact of inlet and outlet flow variations for transonic compressor rotor blades using polynomial chaos. An adaptive sparse grid technique is employed to construct the model of adaptive non-intrusive polynomial chaos (ANIPC). Through statistical evaluation of performance changes for NASA Rotor 67, the response performance of ANIPC is firstly verified. Then the ANIPC is used to evaluate the changes of adiabatic efficiency and mass flow rate of Rotor 67 considering the variations of inlet total pressure and outlet back pressure at different operation conditions. The results reveal that the performance changes exhibit evident nonlinear dependence on the inlet and outlet pressure variations. Moreover, performance changes of the rotor blade in the whole operation range are evaluated and illustrated. Finally, by Monte Carlo simulation, the flow solutions along span and in the blade passage are statistically analyzed to demonstrate the impact mechanisms of inlet and outlet pressure variations to the performance changes.
机译:现实世界中,流动变化对涡轮机械叶片的空气动力学性能的影响是相当大的。空气动力学性能的不确定性量化对于评估平均性能变化,鲁棒设计等有用。本文研究了使用多项式混沌的跨音速压缩机转子叶片的入口和出口流动变化的性能影响。采用自适应稀疏电网技术来构建自适应非侵入式多项式混沌(ANIPC)的模型。通过NASA转子67的性能变化的统计评估,首先验证了ANIPC的响应性能。然后,考虑到不同操作条件下的入口总压力和出口背部压力的变化,ANIPC用于评估转子67的绝热效率和质量流速的变化。结果表明,性能变化表现出明显的非线性依赖于入口和出口压力变化。此外,评估和说明整个操作范围内转子叶片的性能变化。最后,通过蒙特卡罗模拟,跨越跨越叶片通道的流动溶液在统计上分析,以证明入口和出口压力变化对性能变化的冲击机制。

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