基于四象限法的跨声速压气机非设计点损失分析

摘要/Abstract

摘要：

摘要：基于流线曲率法发展了一种适用于跨声速压气机性能预测的高精度模型，对最小损失攻角及非设计点损失预测模型进行了修正.提出了一种非设计点损失分析方法——四象限法，结合该方法对跨声速压气机的损失构成进行了重新定义，对不同工况的损失特点开展了深入分析，在一定程度上揭示了跨声速压气机的损失分布和增长规律.采用新发展的模型对某高负荷跨声速转子进行了详细的计算，并与实验数据进行对比.结果表明，发展的性能预测模型和损失分析方法能够较为可靠地预测全流量工况下跨声速转子的总体性能与气动参数沿展向的分布，为跨声速压气机的特性预测提供了新的思路，具有较强的借鉴意义和工程实用价值.

关键词: 跨声速压气机, 通流计算, 非设计点损失, 最小损失攻角

Abstract:

Abstract： Highly accurate performance prediction models based on the streamline curvature method for the through-flow analysis of transonic compressors was developed, of which the minimum loss incidence and off-design loss prediction model were modified. In addition, four-quadrant -analysis, an original method for off-design loss analysis, was proposed to redefine the composite of transonic compressor loss, to make a further exploration on the characteristic of loss at multiple operating conditions, and to reveal the loss distribution and growth law of transonic compressors to a certain extent. Detailed calculations of a highly loaded transonic compressor rotor with the newly developed model was conducted. The results show that the newly developed model and the four-quadrant-analysis method can reliably predict the overall performance and spanwise distribution of aerodynamic parameters at both design and offdesign operating conditions, providing a new idea for off-design performance prediction. In general, the newly developed model and analysis method can be of great service to engineering.

Key words: transonic compressor, through-flow calculation, off-design loss, minimum loss incidence

中图分类号:

V 231
TK 474

徐玺，羌晓青，滕金芳. 基于四象限法的跨声速压气机非设计点损失分析[J]. 上海交通大学学报（自然版）, 2015, 49(09): 1416-1421.

XU Xi,QIANG Xiaoqing,TENG Jinfang. Off-Design Performance Prediction in a Transonic Axial Compressor Using Four-Quadrant-Analysis[J]. Journal of Shanghai Jiaotong University, 2015, 49(09): 1416-1421.

参考文献

［1］Boyer K M, O’Brien W F. An improved streamline curvature approach for offdesign analysis of transonic axial compression systems［C］∥ASME Turbo Expo 2002. Power for Land, Sea, and Air. America: Society of Mechanical Engineers, 2002: 803811.

［2］Biollo R, Benini E. Shock/boundarylayer/tipclearance interaction in a transonic rotor blade［J］. Journal of Propulsion and Power, 2009, 25(3): 668677.

［3］Pachidis V, Templalexis I, Pilidis P. A dynamic convergence control algorithm for the solution of two dimensional streamline curvature methods［C］∥ASME Turbo Expo 2009. Power for Land, Sea, and Air. America: Society of Mechanical Engineers, 2009: 287296.

［4］Petrovic M V, Wiedermann A, Banjac M B. Development and validation of a new universal through flow method for axial compressors［C］∥ASME Turbo Expo 2009. Power for Land, Sea, and Air. America: Society of Mechanical Engineers, 2009: 579588.

［5］Aungier R H. Axialflow compressor: A strategy for aerodynamic design and analysis ［M］. New York: ASME Press, 2003.

［6］Gill A, Von Backstrom T W, Harms T M. The flow field within an axial flow compressor at extremely high flow coefficients［C］∥ASME Turbo Expo 2010. Power for Land, Sea, and Air. America: Society of Mechanical Engineers, 2010: 355367.

［7］Gill A, Von Backstrm T W, Harms T M. Flow fields in an axial flow compressor during four quadrant operation［J］. Journal of Turbomachinery, 2014, 136(6): 061007.

［8］胡江峰, 欧阳华, 竺晓程, 等. 跨音速压气机非设计点性能预测［J］. 上海交通大学学报, 2010,44(10): 13421346.

HU Jiangfeng, OUYANG Hua, ZHU Xiaocheng, et al. Performance prediction of transonic axial compressor at offdesign points［Ｊ］. Journal of Shanghai Jiaotong Ｕniversity, 2010, 44(10): 13421346.

［9］胡江峰, 竺晓程, 杜朝辉. 一种跨声速轴流压气机性能预测的数值方法［J］. 航空动力学报，2011, 26(1): 122127.

HU Jiangfeng, ZHU Xiaocheng, DU Chaohui. Numerical method of transonic axial compressor performance prediction［J］. Journal of Aerospace Power, 2011, 26(1): 122127.

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