Investigation of improved SA turbulence models for flow in aeroengine compressors
-
摘要:
针对标准SA(Spalart-Allmaras)湍流模型在空天发动机压气机复杂旋转流动预测中精确性不足的问题,系统地分析了SA-helicity修正湍流模型在旋转流动中的适应性,深入揭示了helicity修正项通过跨尺度涡黏抑制机理对主应变率的动态补偿机制,在保持边界层预测精度的同时,实现了角区分离与叶尖泄漏流协同控制准确预测。基于NASA Rotor 67、某高负荷单级压气机以及Aachen三级半压气机的多维度验证体系,针对不同转速下性能特性以及近失速点的叶尖失速和二次流动特征,对比分析标准SA、SA-QCR(quadratic constitutive relation)、SA-helicity这3种湍流模型的工程适应性。研究发现SA-helicity模型和SA-QCR模型均准确预测了特性线变化趋势。SA-helicity模型能在逆压梯度下增加角区分离区涡黏性,抑制角区过大分离,合理预测了叶根分离引发的通道二次流以及叶片下半部压比提升。相较于QCR模型,helicity模型能更合理地预测了叶尖泄漏流发展及范围,显著扩展了流量范围、压比和效率,更符合实验结果。此外,helicity模型预测的边界层流动更能抵抗不利逆压梯度,促使分离泡再附提前,叶尖区域附近扩压能力增强,压比和流量范围显著扩大。整体上,SA-helicity模型成功突破了传统SA湍流模型在压气机流动模拟中对旋转二次流与主流干涉效应预测失准的技术瓶颈。
Abstract:To address the accuracy problems of standard SA (Spalart-Allmaras) turbulence model when predicting complex rotating flows in aviation compressors, how the SA-helicity modified turbulence model performed in rotating flows was analyzed. It showed how the helicity correction helped compensate for strain rate through eddy viscosity mechanisms, leading to better predictions of corner separation and tip leakage flow while maintaining good boundary layer accuracy. Three turbulence models: standard SA, SA-helicity, and SA-QCR (quadratic constitutive relation), were tested, using NASA Rotor 67, a 3.5-stage axial compressor, and a publicly released high-load single-stage axial compressor from AECC Shenyang Engine Research Institute. Their performance at different rotational speeds was analyzed by focusing on performance characteristic curves, tip stall prediction, secondary flow prediction, and near-stall point prediction. Results showed that both the SA-helicity and SA-QCR models accurately predicted the trends of the characteristic curves. The SA-helicity model increased eddy viscosity in the corner separation region under adverse pressure gradients, thereby suppressing excessive corner separation. It also reasonably predicted the channel secondary flow induced by root separation, leading to an increased pressure ratio in the lower half of the blade. Compared with the QCR model, the helicity model better predicted the development and extent of tip leakage flow, significantly expanding the flow range, pressure ratio and efficiency, and showing better agreement with experimental results. Furthermore, the boundary layer flow predicted by the helicity model resisted adverse pressure gradients better, resulting in separation bubble reattaching earlier, thereby enhancing diffusion capability near the tip region and expanding the pressure ratio and flow range. Overall, the SA-helicity model overcame the limitations of traditional turbulence models in predicting how rotating secondary flows interacted with main flows in complex compressor environments.
-
Key words:
- compressor /
- turbulence model /
- performance characteristics /
- corner separation /
- secondary flow /
- tip leakage flow /
- boundary layer
-
表 1 模型常数
Table 1. Model constant value
参数 数值 $ {c}_{\mathrm{b}1} $ 0.1355 $ {c}_{\mathrm{b}2} $ 0.622 $ \sigma $ $ \text{2/3} $ $ \kappa $ 0.41 $ {c}_{\mathrm{w}2} $ 0.3 $ {c}_{\mathrm{w}3} $ 2 $ {c}_{\mathrm{v}1} $ 7.1 $ {c}_{\mathrm{t}3} $ 1.2 $ {c}_{\mathrm{t}4} $ 0.5 $ {c}_{\mathrm{w}1} $ $ \dfrac{{c}_{\mathrm{b}1}}{{\kappa }^{2}}+\dfrac{1+{c}_{\mathrm{b}2}}{\sigma } $ 表 2 NASA Rotor 67几何和性能参数
Table 2. Geometry and performance characteristics of NASA Rotor 67
参数 数值 叶片数 22 展弦比 1.56 设计转速/(r/min) 16043 堵点流量/(kg/s) 34.96 设计点流量/(kg/s) 33.25 设计点总压比 1.63 最高效率/% 93.2 表 3 质量流量(堵点工况)
Table 3. Mass flow rate (choking condition)
湍流模型 质量流量/(kg/s) 标准SA 34.68 SA-helicity 34.65 SA-QCR 34.68 Exp. 34.96 表 4 失稳裕度(100%转速)
Table 4. Stall margin (100% rotation speed)
湍流模型 失稳裕度/% 标准SA 10.75 SA-helicity 20.31 SA-QCR 14.14 Exp. 14.24 表 5 高负荷单级轴流压气机试验性能参数
Table 5. Experimental performance parameters of high loaded 1-stage axial compressor
工况 参数 数值 设计点 转速/(r/min) 9387 质量流量/(kg/s) 32.71 总压比 1.907 等熵效率/% 91.0 最高效率点 等熵效率/% 91.8 近喘点 质量流量/(kg/s) 29.9 总压比 1.931 喘振裕度/% 10.8 叶尖间隙位置 间隙名称 数值 IGV $ {{C}}_{\text{t1}} $ 0.37 $ {{C}}_{\text{h1}} $ 0.23 R1 $ {{C}}_{\text{r1}} $ 1.15 $ {{C}}_{\text{r2}} $ 1.03 S1 $ {{C}}_{\text{t2}} $ 0.55 $ {{C}}_{\text{t3}} $ 0.51 $ {{C}}_{\text{h2}} $ 0.55 $ {{C}}_{\text{h3}} $ 0.43 表 7 606压气机计算网格质量报告
Table 7. Grid quality report of 606 compressor computational grid
计算域 网格数/万 最小倾斜度/(°) 最大长宽比 展向角点网格畸变/(°) 支板 117.1 38.02 2964.2 1.45 进口导叶 116.4 42.41 1192.5 10.16 第1级转子 81.6 16.53 1395.6 11.27 第1级静子 144.6 15.63 2889.0 5.76 表 8 Aachen叶片排设置
Table 8. Aachen blade row setup
参数 IGV R1 S1 R2 S2 R3 S3 叶片数 38 25 40 31 42 39 46 转速/(r/min) 0 17000 0 17000 0 17000 0 叶尖间隙/mm 0 0.2 0 0.2 0 0.2 0 表 9 Aachen计算域网格点分布
Table 9. Grid point distribution of Aachen computational domain
叶片排 网格点数 计算域
网格点数流向 叶片边界层(O block) 周向 径向 IGV 77 21 49 65 460 751 R1 117 21 61 73 683 663 S1 93 21 49 61 555 893 R2 101 21 61 73 581 023 S2 117 17 65 61 461 465 R3 101 21 61 73 581 023 S3 77 21 41 57 406 353 总网格点数 3 730 171 -
[1] 曹建国. 航空发动机仿真技术研究现状、挑战和展望[J]. 推进技术, 2018, 39(5): 961-970. CAO Jianguo. Status, challenges and perspectives of aero-engine simulation technology[J]. Journal of Propulsion Technology, 2018, 39(5): 961-970. (in ChineseCAO Jianguo. Status, challenges and perspectives of aero-engine simulation technology[J]. Journal of Propulsion Technology, 2018, 39(5): 961-970. (in Chinese) [2] WEI Sun. Assessment of advanced RANS turbulence models for prediction of complex flows in compressors[J]. Chinese Journal of Aeronautics, 2023, 36(9): 162-177. doi: 10.1016/j.cja.2023.06.007 [3] CASARTELLI E, MANGANI L, ROOS LAUNCHBURY D, et al. Application of advanced RANS turbulence models for the prediction of turbomachinery flows[J]. Journal of Turbomachinery, 2022, 144(1): 011008. doi: 10.1115/1.4051938 [4] JONAK P, BORZECKI T, KUBACKI S. An investigation of secondary flow features in a low pressure turbine[J]. Journal of Physics: Conference Series, 2018, 1101: 012011. doi: 10.1088/1742-6596/1101/1/012011 [5] YAN Wenhui, SUN Zhaozheng, ZHOU Junwei, et al. Numerical simulation of transonic compressors with different turbulence models[J]. Aerospace, 2023, 10(9): 784. doi: 10.3390/aerospace10090784 [6] GEORGIADIS N J, DEBONIS J R. Navier-Stokes analysis methods for turbulent jet flows with application to aircraft exhaust nozzles[J]. Progress in Aerospace Sciences, 2006, 42(5/6): 377-418. [7] GOURDAIN N, SICOT F, DUCHAINE F, et al. Large eddy simulation of flows in industrial compressors: a path from 2015 to 2035[J]. Philosophical Transactions Series A, Mathematical, Physical, and Engineering Sciences, 2014, 372(2022): 20130323. [8] WANG Danhua, LU Lipeng, LI Qiushi. Improvement on S-A model for predicting corner separation based on turbulence transport nature: AIAA2009-4931[R]. Denver, US: the 45th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 2009. [9] MA Li, LU Lipeng, FANG Jian, et al. A study on turbulence transportation and modification of Spalart-Allmaras model for shock-wave/turbulent boundary layer interaction flow[J]. Chinese Journal of Aeronautics, 2014, 27(2): 200-209. doi: 10.1016/j.cja.2014.02.008 [10] SUN W. Turbulence modelling for complex flows in turbomachinery[D]. Cambridge, UK. University of Cambridge, 2020. [11] LIU Yangwei, LU Lipeng, FANG Le, et al. Modification of Spalart-Allmaras model with consideration of turbulence energy backscatter using velocity helicity[J]. Physics Letters: A, 2011, 375(24): 2377-2381. doi: 10.1016/j.physleta.2011.05.023 [12] KIM S, PULLAN G, HALL C A, et al. Stall inception in low-pressure ratio fans[J]. Journal of Turbomachinery, 2019, 141(7): 071005. doi: 10.1115/1.4042731 [13] LOPEZ D I, GHISU T, KIPOUROS T, et al. Extending highly loaded axial fan operability range through novel blade design[J]. Journal of Turbomachinery, 2022, 144(12): 121009. doi: 10.1115/1.4055350 [14] YU Zhifan, DEFOE J. Validation of helicity-corrected Spalart-Allmaras model for corner separation prediction in incompressible flow with OpenFOAM[J]. Journal of the Global Power and Propulsion Society, 2024, 8: 73-83. doi: 10.33737/jgpps/186057 [15] SPALART P R. Strategies for turbulence modelling and simlations[J]. International Journal of Heat and Fluid Flow, 2000, 21(3): 252-263. doi: 10.1016/S0142-727X(00)00007-2 [16] MENTER F R, MATYUSHENKO A, LECHNER R. Development of a generalized k-ω two-equation turbulence model[C]// New Results in Numerical and Experimental Fluid Mechanics XII. Cham, Germany: Springer International Publishing, 2020: 101-109. [17] SUN Wei, XU Liping. Improvement of corner separation prediction using an explicit non-linear RANS closure[J]. Journal of the Global Power and Propulsion Society, 2021, 5: 50-65. doi: 10.33737/jgpps/133913 [18] CHINA B U, LI Wenhao, LIU Yangwei, et al. Evaluation of Spalart-Allmaras model with various modifications for predicting corner separation in a compressor cascade[C]//Proceedings of Global Power & Propulsion Society. Beijing: GPPS, 2019: V02DT44A040. [19] LI Wenhao, LIU Yangwei. Numerical investigation of corner separation flow using Spalart-Allmaras model with various modifications[J]. Aerospace Science and Technology, 2022, 127: 107682. doi: 10.1016/j.ast.2022.107682 [20] WANG Z, NIEHUIS R. Assessment of numerical methods on a 3.5-stage axial compressor[C]// Proceedings of the 18th International Society for Air Breathing Engines Conference. Beijing: ISABE, 2007: 1452-1461 [21] SPALART P, ALLMARAS S. A one-equation turbulence model for aerodynamic flows: AIAA1992-439[R] Reno, US: AIAA, 1992. [22] 赵宏凯, 方乐, 陆利蓬. 非均衡湍流研究进展[J]. 气体物理, 2018, 3(2): 13-26. ZHAO Hongkai, FANG Le, LU Lipeng. Advances in non-equilibrium turbulence research[J]. Physics of Gases, 2018, 3(2): 13-26. (in ChineseZHAO Hongkai, FANG Le, LU Lipeng. Advances in non-equilibrium turbulence research[J]. Physics of Gases, 2018, 3(2): 13-26. (in Chinese) [23] RUMSEY C L, CARLSON J R, PULLIAM T H, et al. Improvements to the quadratic constitutive relation based on NASA juncture flow data[J]. AIAA Journal, 2020, 58(10): 4374-4384. doi: 10.2514/1.J059683 [24] STRAZISAR A J, POWELL J A. Laser anemometer measurements in a transonic axial flow compressor rotor[J]. Journal of Engineering for Power, 1981, 103(2): 430-437. doi: 10.1115/1.3230738 [25] WADIA A R, SZUCS P N, CRALL D W. Inner workings of aerodynamic sweep[J]. Journal of Turbomachinery, 1998, 120(4): 671-682. doi: 10.1115/1.2841776 [26] HAH C, HATHAWAY M, KATZ J. Investigation of unsteady flow field in a low-speed one and a half stage axial compressor: effects of tip gap size on the tip clearance flow structure at near stall operation[C]// Proceedings of the ASME Turbo Expo. Düsseldorf, Germany: ASME, 2014: DT44A04-V02DT44A04. [27] 刘太秋, 赵月振, 王咏梅, 等. 负荷系数0.5的高负荷单级轴流压气机设计及试验研究[J]. 航空发动机, 2022, 48(5): 1-39. LIU Taiqiu, ZHAO Yuezhen, WANG Yongmei, et al. Design and experimental investigation of a highly loaded single-stage axial compressor with loading coefficient of 0.5[J]. Aeroengine, 2022, 48(5): 1-39. (in ChineseLIU Taiqiu, ZHAO Yuezhen, WANG Yongmei, et al. Design and experimental investigation of a highly loaded single-stage axial compressor with loading coefficient of 0.5[J]. Aeroengine, 2022, 48(5): 1-39. (in Chinese) [28] SWOBODA D, HILDEBRANDT T H. Detailed verification of a 3D Navier-Stokes-solver in industrial design application on a 3 stage axial compressor (Aachen compressor) [C]//Proceedings of Ercoftac/QNET Meeting. Aachen, Germany: ERCOFTAC, 2002: 511-523. [29] WANG Zhuo. Numerical study of a 3.5-stage axial compressor at on-and off-design conditions[J]. Journal of Aerospace Power, 2007, 22(9): 1444-1454. -

下载: