This study investigates a high-loaded axial compressor in which flow instabilities in the rotor and the stator occur almost concurrently.Under these conditions,conventional stability enhancement methods prove to be ineffective.The paper proposes a combined rotor-stator flow control technique.This study reveals that the flow field deterioration stems from combined flow blockage at the rotor tip region and the near-hub region of the stator.Research on flow control methods finds that self-recirculating casing treatment can effectively improve flow capacity in the rotor tip region,but simultaneously reduce flow capacity in the near-hub zone.This makes the hub flow field more susceptible to breakdown and ultimately triggers compressor instability.Thus,the self-recirculating casing treatment fails to enhance stall margin.By contrast,hub suction significantly improves the hub-region flow field.Yet without suppressing the rotor-tip flow blockage,it achieves limited stability enhancement.The integrated solution combining self-recirculating casing treatment with hub suction simultaneously addresses flow blockage at both the rotor tip and the stator near-hub regions.This combined flow control method delivers effective stability enhancement,achieving 6.78%increase in compressor stall margin.

The accumulation of particulate contaminants on compressor airfoils constitutes a critical operational challenge for gas turbine engines, inducing progressive aerodynamic performance degradation. To explore the susceptibility of different regions on the blade surface of axial flow compressor to micrometer-sized particles, accelerated fouling experiments were conducted on a four-stage highly-loaded axial compressor. Performance parameters, including static pressure rise and torque efficiency, were analyzed pre- and post-fouling. Non-contact blue light scanning was used to determine fouling distribution and thickness. Results revealed substantial performance deterioration post-fouling, manifesting as 6.8% reduction in stage static pressure rise and 8.9% decrease in torque efficiency at large flow coefficient condition (φ = 0.73). The performance degradation was mainly attributed to fouling on the leading-edge and pressure surface of the blade, where the maximum fouling thickness reached 0.28 mm. Additionally, the susceptibility of the fouling is influenced by complex three-dimensional flow structures—particularly enhanced accumulation in regions affected by tip leakage vortices and corner separation zones.

The non-axisymmetric deviation of blade stagger angle and tip clearance has significant impact on aerodynamic performance and stability in actual compressors. In this paper, three sets of compressor test, including the prototype with a uniform layout, as well as non-axisymmetric stagger angle and tip clearance layouts, were studied on a four-stage low-speed research compressor test rig. Experimental measurements and numerical simulations were conducted to obtain the overall performance, interstage aerodynamic parameters, and non-axisymmetric properties. The test results show that the two non-axisymmetric layouts reduce compressor efficiency compared with the prototype, but the non-axisymmetric clearance layout increases the prototype stall margin by 0.67%. Numerical simulation analysis reveals that in the near-stall condition, when the low-energy fluid from the large clearance sector passes through the small clearance sector, the high-entropy region is decomposed and the unstable fluid is reconstructed, thus alleviating the stall characteristics. The original measurement data obtained in this paper calibrates the numerical simulation tool and provides a reference for further clarifying the actual flow field characteristics of high-pressure compressors.

Uncertainties in the aerodynamic performance of compressors, introduced by manufacturing variations, have received more and more attentions in recent years. The deviation model plays a crucial role in evaluating this uncertainty and facilitating robust design. However, current deviation models with a few variables cannot simultaneously achieve a precise geometric approximation of deviation and provide an accurate assessment of performance uncertainty. This paper introduces a novel deviation modeling method named Nested Principal Component Analysis (NPCA) to break this tradeoff. In this method, both geometry-based and performance-based modes are utilized to describe manufacturing variations. By considering aerodynamic sensitivity, surface deformations that significantly impact aerodynamic performance can be extracted for deviation modeling. To demonstrate the superiority of this newly proposed method, ninety-eight newly manufactured compressor rotor blades were measured using a coordinate measurement machine, and both NPCA and Principal Component Analysis (PCA) were employed to model the real manufacturing variations. The results indicate that, in comparison to the PCA method, the NPCA method achieves an equivalent level of accuracy in geometric reconstruction and evaluation of mean performance. Furthermore, the same level of accuracy can be obtained with eight NPCA modes and fifty PCA modes when assessing the scatter in aerodynamic performance. Finally, the working mechanism of the NPCA method for accurate uncertainty quantification was further investigated.

Manufacture variations can greatly increase the performance variability of compressor blades. Current robust design optimization methods have a critical role in reducing the adverse impact of the variations, but can be affected by errors if the assumptions of the deviation models and distribution parameters are inaccurate. A new approach for robust design optimization without the employment of the deviation models is proposed. The deviation package method and the interval estimation method are exploited in this new approach. Simultaneously, a stratified strategy is used to reduce the computational cost and assure the optimization accuracy. The test case employed for this study is a typical transonic compressor blade profile, which resembles most of the manufacture features of modern compressor blades. A set of 96 newly manufactured blades was measured using a coordinate measurement machine to obtain the manufacture variations and produce a deviation package. The optimization results show that the scatter of the aerodynamic performance for the optimal robust design is 20% less than the baseline value. By comparing the optimization results obtained from the deviation package method with those obtained from widely-used methods employing the deviation model, the efficiency and accuracy of the deviation package method are demonstrated. Finally, the physical mechanisms that control the robustness of different designs were further investigated, and some statistical laws of robust de-sign were extracted.

Aerodynamic uncertainties in compressors introduced by manufacturing variability have garnered increasing attention in recent years. Accurately assessing the impact of manufacturing variations on newly designed blades is essential for facilitating robust design. However, the assessment of performance uncertainty of designed blades is significantly influenced by the method employed to introduce geometric uncertainty. This paper investigates the appropriate approach for superimposing manufacturing variations onto new blade profiles to obtain accurate insights into aerodynamic uncertainties. The first part of the paper thoroughly analyzes manufacturing variations in over 1400 newly manufactured rotor blades from different compressor stages, which were measured using a coordinate measurement machine. The statistical characteristics of geometric variations in distinct directions are captured. In the second part, by calculating the aerodynamic performance of numerous compressor blade profiles with manufacturing variability, we investigate the interchangeability of manufacturing variations from different compressor stages for accurately assessing the aerodynamic uncertainties of new designs. The results demonstrate that manufacturing variations among different stages exhibit some similar geometric characteristics and are easily interchangeable when evaluating mean performance. When assessing the standard deviation of aerodynamic performance, the statistical results corresponding to the manufacturing variations from different stages exhibit a consistent trend, with some discrepancies emerging under different operating conditions.

Studies on the geometry variation-related compressor uncertainty quantification (UQ) have often used dimension reduction methods, such as the principal component analysis (PCA), for the modeling of deviations. However, in the PCA method, the main eigenmodes were determined based only on the statistical behavior of geometry variations. While this process can cause some missing modes with a small eigenvalue, it is much more sensitive to blade aerodynamic performances, and thereby reducing the reliability of the UQ analysis. Hence, a novel geometry variation modeling method, named sensitivity-correlated principal component analysis (SCPCA), has been proposed. In addition, by means of the blade sensitivity analysis, the weighting factors for each eigenmode were determined and then used to modify the process of the PCA. As a result, by considering the covariance of geometry variations and the performance sensitivity, the main eigenmodes could be determined and used to reconstruct the blade samples in the UQ analysis. With 98 profile samples measured at the midspan of a high-pressure compressor rotor blade, both the PCA and SCPCA methods were employed for the UQ analysis. The results showed that, compared to the PCA method, the SCPCA method provided a more accurate reconstruction of sensitive deviations, leading to an 11.8% improvement in evaluating the scatter of the positive incidence range, while also maintaining the accuracy of the uncertainty assessment for other performances.

Compressed air energy storage systems must promptly adapt to power network demand fluctuations, necessitating a high surge margin in the compression system to ensure safety. It is challenging to completely eliminate blade geometric variations caused by limited machining precision, the important effects of which should be considered during aerodynamic shape design and production inspection. The present paper explores the uncertainty impact of geometric deviations on the stability margin of a multi-stage axial compressor at a low rotational speed. Initially, an adaptive polynomial chaos expansion-based universal Kriging model is introduced, and its superior response performance in addressing high-dimensional uncertainty quantification problems is validated through rigorous analytical and engineering tests. Then, this model is used to statistically evaluate the stability margin improvement (SMI) of the compressor due to the Gaussian and realistic geometric variabilities separately. The results show that the mean and standard deviation of SMI are −0.11% and 0.5% under the Gaussian geometric variability, while those are 0.33% and 0.39% under the realistic variability. For both the geometric variabilities, the stagger angle and maximum thickness deviations of the first-stage rotor are the most influential parameters controlling the uncertainty variations in the stability margin. Finally, the underlying impact mechanism of the influential geometric deviations is investigated. The variation in the stability margin caused by the geometric deviations primarily results from the alteration of inlet incidences, affecting the size of the tip leakage vortex blockage and boundary-layer separation regions near the blade tip of the first-stage rotor.

以涵道可调发动机为基础,通过单双外涵工作模式多涵道压缩系统联合数值模拟,研究了实现模式选择阀被动调节的气动匹配方法及其对压缩系统的影响.结果表明:设计工况气动匹配可以提供足够的模式选择阀气动力以维持单双外涵工作模式,单外涵转双外涵时模式选择阀启动压差很容易建立,而双外涵转单外涵时模式选择阀启动压差较难建立且易使压缩部件稳定裕度下降,是实现模式选择阀被动调节的难点.综合考虑压缩部件稳定性和模式选择阀所受气动力特点,提出了一种适用于工程应用的模式选择阀被动调节方案.

In this paper, an adaptive sparse arbitrary polynomial chaos expansion (PCE) is first proposed to quantify the performance impact of realistic multi-dimensional manufacturing uncertainties. The Stieltjes algorithm is employed to generate the PCE basis functions concerning geometric variations with arbitrary distributions. The basis-adaptive Bayesian compressive sensing algorithm is introduced to retain a small number of significant PCE basis functions, requiring fewer model training samples while preserving fitting accuracy. Second, several benchmark tests are used to verify the computational efficiency and accuracy of the proposed method. Eventually, the coexistence effects of six typical machining deviations on the aerodynamic performance and flow fields of a controlled diffusion compressor cascade are investigated. The probability distributions of the machining deviations are approximated by limited measurement data using kernel density estimation. By uncertainty quantification, it can be learned that the mean performance seriously deteriorates with increasing incidences, while the performance at negative incidences is more dispersed. By global sensitivity analysis, the leading-edge profile error should be given high priority when working at negative incidences, and the inlet metal angle error would be carefully inspected first when the cascade works at high positive incidences. Furthermore, controlling the manufacturing accuracy of the suction surface profile error can play a certain role in improving the robustness of aerodynamic performance in off-design conditions. Through flow field analysis, it further proves that actual leading-edge errors are the most important ones to aerodynamics and reveals how the effects of leading-edge errors propagate in the cascade passage, thus affecting the aerodynamic loss.

The impact of geometric deviation due to manufacturing on compressor performance is considerable in engineering practice. To investigate the impact of blade thickness deviation on compressor performance and flow loss at various rotational speeds, a three-dimensional steady numerical simulation on Rotor 37 was conducted. The quantification of uncertainty was accomplished using a non-intrusive polynomial chaos method. The viscous dissipation coefficient was introduced to analyze the uncertain influence of blade thickness deviation on flow loss. Based on the type of loss source, the flow field was divided into six regions, including the blade tip region, blade root region, leading edge region, trailing edge region, blade surface region, and mainstream region. The results indicate that the sensitivity of total pressure ratio to thickness deviation increases significantly with an increase in the rotational speed. Under peak efficiency conditions, the effect of blade thickness deviation on flow dissipation in leading edge region decreases initially and then increases with an increase in the rotational speed. Meanwhile, the impact on flow loss in other regions increases with the increase in the rotational speed. Under near stall conditions, the blade thickness deviation has a great impact on the flow losses in the blade tip region, leading edge region, and mainstream region at 60% design rotational speed. However, the blade tip region and trailing edge region are more noticeably affected at 100% design rotational speed. Furthermore, the quantification of standard deviation of flow losses in various regions under different rotational speeds and conditions reveals that the flow loss fluctuation in the leading edge region and mainstream region varies with changes in operating conditions and rotational speeds, but the fluctuation of flow loss in other regions is independent of the rotational speed.

The aerodynamic design of multi-stage transonic axial-flow compressors plays a critical role in the overall performance of aeronautical engine, gas turbine and industry compression unit. Despite a series of new design methods have been successfully proposed in the research and development of advanced axial-flow compressors, redesign methods are still one of the most effective measures in the development of available advanced products to meet new requirements. In this work, a geometry scaling technique is proposed in which 1D mean-line analysis and 3D parametric geometric modeling are used to define a series of key redesign criteria with as minor variations as possible in the aerodynamic performance compared against the original design. The motivation behind this technique is to develop a CFD validation rig while keep both the aerodynamic performance and CFD prediction accuracy unchanged with reduced partial annulus model. The proposed scaling technique is then verified by the redesign of a 3.5-stage transonic axial-flow compressor with geometry scaling of blade/vane numbers and IGV-rotor-stator axial spacing. The CFD prediction shows that the variation in overall performance of redesigned compressors is generally within one percent, verifying the effectiveness of the proposed scaling technique.

基于双外涵变循环发动机压缩系统,分析了多连通气动布局变循环压缩系统的匹配工作机制.一体化全三维数值模拟表明:变循环压缩系统各压缩部件与涵道及其调节机构之间由于多连通特征相对于常规发动机压缩系统具有更强的耦合工作特点,高效的外涵道流动是发挥变循环发动机性能优势的关键.涵道几何的调节不仅会改变其自身流动状态,还伴随着压缩部件气动性能的偏移,模式转换过程必须符合各涵道及调节机构之间的气动协调匹配.提出了适用于多连通变循环压缩系统的一体化变维度分析方法,将部件通流程序与涵道零维程序相结合,实现了部件-涵道耦合匹配关系的快速分析.基于变维度分析方法给出了单外涵模式部件与涵道共同约束下的压缩系统综合匹配可行域,旨在为变循环发动机的匹配设计提供理论依据.

采用挡板产生压力畸变,以三级风扇为平台研究风扇抗畸变性能.试验结果表明,畸变敏感系数随换算转速的变化与畸变指数相关,不同畸变指数下风扇畸变敏感系数并不唯一,最大变化量超过40％.依据试验结果,分析畸变指数、稳态与动态畸变指数比例、畸变敏感系数、畸变衰减等随换算转速或挡板堵塞比的变化规律,初步探讨了风扇特性线形状对其抗压力畸变能力的影响.基于试验结果,针对三级风扇开展了15％挡板堵塞比下的数值仿真研究,初步研究了压力畸变的产生过程及压力畸变在风扇内部衰减并产生温度畸变的过程.数值仿真结果表明,设计转速工作点第一级转子出口总温不均匀性大于15％.

为了研究级间引气对多级轴流压气机性能和流场的影响机理,基于北京航空航天大学的四级低速大尺寸压气机实验台,在二级静子出口进行周向槽引气,采用分别保持引气位置上游流量不变和引气位置下游流量不变两种比较方式,针对不同引气流量大小对压气机性能和内部流场的影响进行了实验研究.结果表明,级间引气会影响压气机压升特性和失速裕度,影响程度与引气量大小有关.级间引气对引气位置上游转子流场的影响表现在上游压气机工况的变化上,上游转子流场的展向分配并不受到引气的影响.引气位置下游受到引气和上游压气机工况变化的共同影响,且引气量越大,影响程度越大.此外,级间引气可以改善下游叶片叶尖区域的流动环境,增强叶尖处流通能力,提高下游压气机失速裕度.

为深入研究不同类型搭接网格对周向槽处理机匣数值模拟结果的影响,以单级跨声速压气机及其转子叶顶的周向槽处理机匣为研究对象,划分了多种计算网格并采用不同类型搭接网格关联周向槽与压气机主流道.三维定常数值模拟和分析表明,传统完全非匹配搭接网格在计算上会导致流场数据通过搭接网格传递时明显失真,使转子尖部复杂流动呈现显著间断特征,给压气机内流和性能模拟结果带来较大不确定性;增强搭接网格匹配度,有利于提高流场数据传递精度,弱化转子尖部复杂流动的不连续性,降低模拟结果的不确定性;采用完全匹配类型搭接网格,可在计算上完全避免搭界网格上的流场数据传递失真,从而使压气机内流及性能模拟结果具有更高的可信度.

以高压压气机出口级叶片叶中截面作为研究对象,获得了实际压气机叶片加工偏差的分布特征,并分析了实际加工偏差对叶型气动性能的影响.以此为基础,研究了加工偏差对叶型性能的影响机理.研究结果表明,实际叶型加工偏差存在一定的系统性偏差,从而导致实际叶型气动性能的平均值偏离设计值.叶型偏差对叶型气动性能的影响存在一定的非线性效应,这在前缘区域更为明显,从而导致了平均叶型的气动性能与实际叶型平均性能出现了明显偏差.前缘附近的几何偏差对吸力面和压力面的速度峰值有较大的影响,因此前缘附近的偏差是使叶型的气动性能产生系统性偏差和增大不确定度的主要因素.根据对流动机理的分析,进口几何角偏差是导致叶型性能出现系统性偏差的主要原因;可以近似用均匀偏差来估计叶身加工偏差对正负攻角范围和损失的影响.

为了满足多级轴流压气机性能预估需求,在一个流线曲率程序基础上开展了经验、半经验关系式研究.通过对文献中的损失模型进行校验及融合,建立了相匹配的损失计算模块,并改进了端壁损失计算方法;研究了利用S1流面计算修正S2正问题的方法,解决了基于传统平面叶栅试验数据的攻角、落后角模型与先进技术叶型之间不匹配的问题,继而发展出了一个高精度的S2正问题计算方法.为了验证计算方法,利用3个不同负荷水平的、经试验验证的多级压气机进行了校验计算.对比表明,发展的程序对多级压气机具有很高的计算精度和稳定性,可用于多级轴流压气机性能分析.

为了验证多级轴流压气机出口级性能,开展四级重复级低速模拟气动设计,并坚持以二维设计为主,三维数值验证为辅.利用相同的设计系统,建立了高低速压气机之间相似的二维流场和叶表无量速度分布.随后,低速与高速压气机三维数值计算结果对比表明,压升系数特性吻合,流场相似,且叶表无量纲速度由设计点到失速点保持一致的变化趋势,进一步验证了二维设计的可行性;利用相同的系统设计高、低速压气机,有利于形成高速-低速-高速的良性循环,有利于完善基于通流程序的设计体系,积累设计经验.