基于数据驱动的扭转度偏差对压气机性能的影响

doi:10.7527/S1000-6893.2023.29938

Abstract

Abstract:

To investigate the impact of introducing changes in the dimensionality and correlation of twist deviation on the quantitative results of compressor performance， we adopt a data-driven non-intrusive polynomial chaos method to quantitatively study the uncertainty effect of blade twist deviation on the aerodynamic performance of a single-stage axial subsonic compressor based on the measurement results of twist deviation of a certain compressor rotor blade， and conduct sensitivity analysis. The research results indicate that the standard deviation of compressor performance under various operating conditions decreases with the increase of the twist deviation dimension introduced. Through quantitative comparison， it was observed that considering twist deviations of the blade tip and root sections is sufficient to ensure the convergence of compressor performance standard deviation and performance probability distribution form. However， in sensitivity analysis， it was revealed that more dimensions of twist deviation introduced can lead to more accurate identification of the most sensitive twist deviation region in compressor performance. As the correlation between twist deviations on various sections gradually strengthens， the fluctuation degree of compressor performance under different operating conditions also increases. Though the difference between the first-order sensitivity indices of compressor performance to twist deviations gradually decreases， the ranking of compressor performance sensitivity to twist deviations on various sections remains unchanged.

Key words: data driven, twist deviation, uncertainty quantification, sensitivity analysis, compressor

CLC Number:

V231.3

Tianyuan JI, Wuli CHU, Haoguang ZHANG, Zhengtao GUO, Dejun MENG. Effect of data-driven twist deviation on compressor performance[J]. Acta Aeronautica et Astronautica Sinica, 2024, 45(19): 629938.

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参数	100%设计转速	71%设计转速
旋转速度/（r·min^-1）	15 200	10 765
设计质量流量/（kg·s^-1）	5.6	4.5
设计总压比	1.249	1.12
设计等熵效率	0.905	0.92
叶尖相对马赫数	0.78	0.7
叶片数	30	30
轮毂比	0.61	0.61
平均展弦比	1.94	1.94
叶顶间隙/mm	0.35	0.35

参数	数值
主通道网格结构	O-4H型网格
径向网格节点	85
轴向网格节点	177
周向网格节点	53
叶顶间隙网格结构	蝶形网格
叶顶间隙内径向网格节点	17
壁面第1层网格厚度/m	2×10^-6
y⁺	<2
网格总数/10⁴	102

参数	数值
湍流模型	Spalart-Allmaras模型
空间离散格式	2阶迎风格式
时间离散格式	显式4阶Runge-Kutta格式
入口气流方向	径向方向
入口总温/K	288
入口总压/Pa	101 325
壁面条件	绝热无滑移边界

叶高截面	分布区间/（°）	平均值/（°）	标准差/（°）
95%	［-0.448， 0.336］	-0.020 00	0.178 89
50%	［-0.493， 0.413］	-0.014 84	0.203 74
5%	［-0.476， 0.340］	-0.033 21	0.185 13

叶片组	Spearman相关系数
叶片组	95%和50%叶高截面	95%和5%叶高截面	50%和5% 叶高截面
G4	0.222 4	0.285 3	0.286 4
G5	0.522 4	0.585 3	0.586 4
G6	0.822 4	0.885 3	0.886 4

Effect of data-driven twist deviation on compressor performance

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