加工误差对超声速叶栅气动性能影响的不确定性分析

刘铠烨; 楚武利; 郭正涛; 梁彩云; 孟德君

doi:10.13224/j.cnki.jasp.20220791

加工误差对超声速叶栅气动性能影响的不确定性分析

doi: 10.13224/j.cnki.jasp.20220791

1.
西北工业大学动力与能源学院，西安 710129
2.
中国航发沈阳发动机研究所，沈阳 110015

基金项目: 国家科技重大专项（J2019-Ⅰ-0011）

详细信息

作者简介:
刘铠烨（1999-），男，硕士生，研究方向为叶轮机械气动热力学

通讯作者:
楚武利（1962-），男，教授、博士生导师，博士，研究领域为高性能轴流及离心压气机先进流动控制。E-mail：wlchu@nwpu.edu.cn

中图分类号: V231.3
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- 文章访问数: 11
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- 被引次数: 0
出版历程
- 收稿日期: 2022-10-14
- 网络出版日期: 2024-04-26

Uncertainty analysis of effects of manufacturing errors on aerodynamic performance of supersonic cascades

1.
School of Power and Energy，Northwestern Polytechnical University，Xi’an 710129，China
2.
Shenyang Engine Research Institute，Aero Engine Corporation of China，Shenyang 110015，China

摘要

摘要:
为了研究法向加工误差对超声速叶栅气动性能的影响，基于高斯过程和主成分分析法，构建了由法向加工误差导致的叶表五维几何不确定性模型。采用基于高斯分布型的非嵌入式混沌多项式方法，结合稀疏网格技术，构建了叶栅性能的代理模型，并预测了加工误差对超声速叶栅气动性能的影响。研究中，还提出了一种量化叶栅流场各部分损失的损失源模型。结果表明：在随机加工误差影响下，超声速叶栅总压损失系数近似于正态分布。总压损失系数对前缘部分的加工误差最为敏感，对吸力面加工误差的敏感程度高于压力面加工误差，并且敏感性沿弦向位置向后逐渐递减。影响机理是，前缘加工误差会影响弓形激波强度以及前缘加速过程，从而影响槽道激波结并构造成叶栅损失出现较大偏差。
- 超声速叶栅 /
- 法向加工误差 /
- 非嵌入式混沌多项式 /
- 不确定性量化分析 /
- 气动性能
Abstract:
To study the effects of normal manufacturing error on the aerodynamic performance of supersonic cascade, a model of five-dimensional blade surface geometric variability from normal manufacturing errors was constructed based on Gaussian process and principal component analysis. Combined with the non-intrusive polynomial chaos expansion based on Gaussian distribution and the sparse grid technique, a surrogate mode of cascade performance was proposed. Then, the effects of manufacturing error on the aerodynamic performance of supersonic cascade were predicted by the surrogate model. A loss source model was also proposed to quantify the loss of each part of cascade flow field. The results showed that the total pressure loss coefficient of supersonic cascade was approximately normal distribution under the effects of random manufacturing error. The total pressure loss coefficient was most sensitive to the manufacturing error of the leading edge, and more sensitive to the manufacturing error of the suction surface than to the manufacturing error of the pressure surface, and the sensitivity gradually decreased backward along the chord. According to the mechanism, the leading edge manufacturing error may affect the bow shock wave strength and the leading edge acceleration process, thus affecting the passage shock pattern and forming a cascade loss with a large deviation.
- supersonic cascade /
- normal manufacturing error /
- non-intrusive polynomial chaos /
- uncertainty quantification /
- aerodynamic performance

HTML

图 1 法向加工误差示意图

Figure 1. Schematic of normal manufacturing error

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图 2 计算域和网格示意图

Figure 2. Schematic of computational domain and grid

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图 3 叶栅上游马赫数分布

Figure 3. Mach number in upstream of cascade

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图 4 不同网格数量对叶表等熵马赫数的影响

Figure 4. Effect of different mesh schemes on isentropic Mach number on blade surface

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图 5 叶栅波系结构

Figure 5. Shock wave pattern of cascade

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图 6 ARL-SL19叶栅“唯一攻角”曲线

Figure 6. Unique incidence curves of ARL-SL19 cascade

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图 7 损失源划分模型

Figure 7. Loss divided for loss sources analysis model

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图 8 不同h取值下特征值分布

Figure 8. Distribution of eigenvalue with different h

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图 9 累计方差贡献率分布

Figure 9. Distribution of cumulative variance contribution rate

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图 10 标准差函数以及均值函数分布

Figure 10. Distribution of standard deviation function and mean function

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图 11 叶表法向加工误差分布

Figure 11. Distribution of normal manufacturing error of blade profile

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图 12 总压损失系数计算值与预测值对比

Figure 12. Comparison of calculation and prediction results of total pressure loss coefficient

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图 13 总压损失系数统计直方图

Figure 13. Histogram of total pressure loss coefficient

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图 14 法向加工误差与总压损失系数敏感性分析

Figure 14. Sensitivity of normal manufacturing error to total pressure loss coefficient

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图 15 叶型型线对比

Figure 15. Comparison of cascade profile

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图 16 损失源分布对比

Figure 16. Comparison of loss sources

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图 17 波系结构对比

Figure 17. Comparison of shock wave patterns

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图 18 叶表摩擦系因对比

Figure 18. Comparison of wall friction factor on blade surface

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图 19 叶表等熵马赫数对比

Figure 19. Comparison of isentropic Mach number on blade surface

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表 1 稀疏网格和全网格配置点数

Table 1. Number of collocation points of sparse grid and full grid

$ d $	k=2		k=3
$ d $	NSG	NFG	NSG	NFG
3	25	27	69	64
5	61	243	241	1024
8	145	6561	849	65536
10	221	59049	1771	1048576

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表 2 叶栅ARL-SL19几何参数

Table 2. Geometric features of ARL-SL19 cascade

参数	数值
弦长/mm	85
稠度	1.53
安装角/（°）	56.93

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表 3 不同损失源的占比

Table 3. Loss source of different schemes

损失源	占比/%	损失源	占比/%
$ {\zeta _{{\mathrm{LE}}}} $	14.8	$ {\zeta _{{\mathrm{1stshock}}}} $	15.4
$ {\zeta _{{\mathrm{BL}}}} $	11.4	$ {\zeta _{{\mathrm{2ndshock}}}} $	9.1
$ {\zeta _{{\mathrm{SS}}}} $	9.4	$ {\zeta _{{\mathrm{TE}}}} $	14.8
$ {\zeta _{{\mathrm{PS}}}} $	2.3

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表 4 总压损失系数不确定性量化统计结果

Table 4. Statistical outputs of uncertainty quantification of total pressure loss coefficient

参数	数值
均值	0.134262
标准差	0.005722

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