Numerical study of corner separation in a linear compressor cascade using various turbulence models

Three-dimensional corner separation is a common phenomenon that significantly affects compressor performance.Turbulence model is still a weakness for RANS method on predicting corner separation flow accurately.In the present study,numerical study of corner separation in a linear highly loaded prescribed velocity distribution(PVD) compressor cascade has been investigated using seven frequently used turbulence models.The seven turbulence models include Spalart–Allmaras model,standard k–e model,realizable k–e model,standard k–x model,shear stress transport k–x model,v~2–f model and Reynolds stress model.The results of these turbulence models have been compared and analyzed in detail with available experimental data.It is found the standard k–e model,realizable k–e model,v~2–f model and Reynolds stress model can provide reasonable results for predicting three dimensional corner separation in the compressor cascade.The Spalart–Allmaras model,standard k–x model and shear stress transport k–x model overestimate corner separation region at incidence of 0°.The turbulence characteristics are discussed and turbulence anisotropy is observed to be stronger in the corner separating region.     

Improvement of Baldwin-Lomax turbulence model for supersonic complex flows

Entropy represents the dissipation rate of energy. Through direct numerical simulation (DNS) of supersonic compression ramp flow, we find the value of entropy is monotonously decreasing along the wall-normal direction no matter in the attached or the separated region. Based on this feature, a new version of Baldwin-Lomax turbulence model (BL-entropy) is proposed in this paper. The supersonic compression ramp and cavity-ramp flows in which the original Baldwin-Lomax model fails to get convergent solutions are chosen to evaluate the performance of this model. Results from one-equation Spalart-Allmaras model (SA) and two-equation Wilcox k-x model are also included to compare with available experimental and DNS data. It is shown that BLentropy could conquer the essential deficiency of the original version by providing a more physically meaningful length scale in the complex flows. Moreover, this method is simple, computationally efficient and general, making it applicable to other models related with the supersonic boundary layer.     

Aerodynamic shape optimization for alleviating dynamic stall characteristics of helicopter rotor airfoil

In order to alleviate the dynamic stall effects in helicopter rotor, the sequential quadratic programming(SQP) method is employed to optimize the characteristics of airfoil under dynamic stall conditions based on the SC1095 airfoil. The geometry of airfoil is parameterized by the class-shape-transformation(CST) method, and the C-topology body-fitted mesh is then automatically generated around the airfoil by solving the Poisson equations. Based on the grid generation technology, the unsteady Reynolds-averaged Navier-Stokes(RANS) equations are chosen as the governing equations for predicting airfoil flow field and the highly-efficient implicit scheme of lower–upper symmetric Gauss–Seidel(LU-SGS) is adopted for temporal discretization. To capture the dynamic stall phenomenon of the rotor more accurately, the Spalart–Allmaras turbulence model is employed to close the RANS equations. The optimized airfoil with a larger leading edge radius and camber is obtained. The leading edge vortex and trailing edge separation of the optimized airfoil under unsteady conditions are obviously weakened, and the dynamic stall characteristics of optimized airfoil at different Mach numbers, reduced frequencies and angles of attack are also obviously improved compared with the baseline SC1095 airfoil. It is demonstrated that the optimized method is effective and the optimized airfoil is suitable as the helicopter rotor airfoil.     

Online condition diagnosis for a two-stage gearbox machinery of an aerospace utilization system using an ensemble multi-fault features indexing approach

China manned space station is designed to operate for over ten years. Long-term and sustainable research on space science and technology will be conducted during its operation. The application payloads must meet the ‘‘long life and high reliability" mission requirement. Gearbox machinery is one of the essential devices in an aerospace utilization system, failure of which may lead to downtime loss even during some disastrous catastrophes. A fault diagnosis of gearbox has attracted attentions for its significance in preventing catastrophic accidents and guaranteeing sufficient maintenance. A novel fault diagnosis method based on the Ensemble Multi-Fault Features Indexing(EMFFI) approach is proposed for the condition monitoring of gearboxes. Different from traditional methods of signal analysis in the one-dimensional space, this study employs a supervised learning method to determine the faults of a gearbox in a two-dimensional space using the classification model established by training the features extracted automatically from diagnostic vibration signals captured. The proposed method mainly includes the following steps. First, the vibration signals are transformed into a bi-spectrum contour map utilizing bi-spectrum technology,which provides a basis for the following image-based feature extraction. Then, Speeded-Up Robustness Feature(SURF) is applied to automatically extract the image feature points of the bi-spectrum contour map using a multi-fault features indexing theory, and the feature dimension is reduced by Linear Discriminant Analysis(LDA). Finally, Random Forest(RF) is introduced to identify the fault types of the gearbox. The test results verify that the proposed method based on the multi-fault features indexing approach achieves the target of high diagnostic accuracy and can serve as a highly effective technique to discover faults in a gearbox machinery such as a two-stage one.     

Static Frame Model Validation with Small Samples Solution Using Improved Kernel Density Estimation and Confidence Level Method

An improved method using kernel density estimation (KDE) and confidence level is presented for model validation with small samples. Decision making is a challenging problem because of input uncertainty and only small samples can be used due to the high costs of experimental measurements. However, model validation provides more confidence for decision makers when improving prediction accuracy at the same time. The confidence level method is introduced and the optimum sample variance is determined using a new method in kernel density estimation to increase the credibility of model validation. As a numerical example, the static frame model validation challenge problem presented by Sandia National Laboratories has been chosen. The optimum bandwidth is selected in kernel density estimation in order to build the probability model based on the calibration data. The model assessment is achieved using validation and accreditation experimental data respectively based on the probability model. Finally, the target structure prediction is performed using validated model, which are consistent with the results obtained by other researchers. The results demonstrate that the method using the improved confidence level and kernel density estimation is an effective approach to solve the model validation problem with small samples.     

CFD Study of NO_x Emissions in a Model Commercial Aircraft Engine Combustor

Air worthiness requirements of the aircraft engine emission bring new challenges to the combustor research and design. With the motivation to design high performance and clean combustor, computational fluid dynamics (CFD) is utilized as the powerful design approach. In this paper, Reynolds averaged Navier-Stokes (RANS) equations of reactive two-phase flow in an experimental low emission combustor is performed. The numerical approach uses an implicit compressible gas solver together with a Lagrangian liquid-phase tracking method and the extended coherent flamelet model for turbulence-combustion interaction. The NOx formation is modeled by the concept of post-processing, which resolves the NOx transport equation with the assumption of frozen temperature distribution. Both turbulence-combustion interaction model and NOx formation model are firstly evaluated by the comparison of experimental data published in open literature of a lean direct injection (LDI) combustor. The test rig studied in this paper is called low emission stirred swirl (LESS) combustor, which is a two-stage model combustor, fueled with liquid kerosene (RP-3) and designed by Beihang University (BUAA). The main stage of LESS combustor employs the principle of lean prevaporized and premixed (LPP) concept to reduce pollutant, and the pilot stage depends on a diffusion flame for flame stabili-zation. Detailed numerical results including species distribution, turbulence performance and burning performance are qualita-tively and quantitatively evaluated. Numerical prediction of NOx emission shows a good agreement with test data at both idle condition and full power condition of LESS combustor. Preliminary results of the flame structure are shown in this paper. The flame stabilization mechanism and NOx reduction effort are also discussed with in-depth analysis.     

Fault detection of flywheel system based on clustering and principal component analysis

Considering the nonlinear, multifunctional properties of double-flywheel with closedloop control, a two-step method including clustering and principal component analysis is proposed to detect the two faults in the multifunctional flywheels. At the first step of the proposed algorithm,clustering is taken as feature recognition to check the instructions of ‘‘integrated power and attitude control" system, such as attitude control, energy storage or energy discharge. These commands will ask the flywheel system to work in different operation modes. Therefore, the relationship of parameters in different operations can define the cluster structure of training data. Ordering points to identify the clustering structure(OPTICS) can automatically identify these clusters by the reachability-plot. K-means algorithm can divide the training data into the corresponding operations according to the reachability-plot. Finally, the last step of proposed model is used to define the relationship of parameters in each operation through the principal component analysis(PCA) method.Compared with the PCA model, the proposed approach is capable of identifying the new clusters and learning the new behavior of incoming data. The simulation results show that it can effectively detect the faults in the multifunctional flywheels system.     

A compositional method to model dependent failure behavior based on PoF models

In this paper, a new method is developed to model dependent failure behavior among failure mechanisms. Unlike the existing methods, the developed method models the root cause of the dependency explicitly, so that a deterministic model, rather than a probabilistic one, can be established. Three steps comprise the developed method. First, physics-of-failure(PoF) models are utilized to model each failure mechanism. Then, interactions among failure mechanisms are modeled as a combination of three basic relations, competition, superposition and coupling. This is the reason why the method is referred to as ‘‘compositional method". Finally, the PoF models and the interaction model are combined to develop a deterministic model of the dependent failure behavior. As a demonstration, the method is applied on an actual spool and the developed failure behavior model is validated by a wear test. The result demonstrates that the compositional method is an effective way to model dependent failure behavior.     

Prediction of shock-layer ultraviolet radiation for hypersonic vehicles in near space

A systemic and validated model was developed to predict ultraviolet spectra features from the shock layer of near-space hypersonic vehicles in the ‘‘solar blind" band region. Computational procedures were performed with 7-species thermal non-equilibrium fluid mechanics, finite rate chemistry, and radiation calculations. The thermal non-equilibrium flow field was calculated with a two-temperature model by the finite volume technique and verified against the bow-shock ultra-violet(BSUV) flight experiments. The absorption coefficient of the mixture gases was evaluated with a line-by-line method and validated through laboratory shock tube measurements. Using the line of sight(LOS) method, radiation was calculated from three BSUV flights at altitudes of 38,53.5 and 71 km. The investigation focused on the level and structure of ultraviolet spectra radiated from a NO band system in wavelengths of 200–400 nm. Results predicted by the current model show qualitative spatial agreement with the measured data. At a velocity of 3.5 km/s(about Mach11), the peak absolute intensity at an altitude of 38 km is two orders of magnitude higher than that at 53.5 km. Under the same flight conditions, the spectra structures have quite a similar distribution at different viewing angles. The present computational model performs well in the prediction of the ultraviolet spectra emitted from the shock layer and will contribute to the investigation and analysis of radiative features of hypersonic vehicles in near space.     

Thermal comfort assessment in civil aircraft cabins

Aircraft passengers are more and demanding in terms of thermal comfort. But it is not yet easy for aircraft crew to control the environment control system(ECS) that satisfies the thermal comfort for most passengers due to a number of causes. This paper adopts a corrected predicted mean vote(PMV) model and an adaptive model to assess the thermal comfort conditions for 31 investigated flights and draws the conclusion that there does exist an uncomfortable thermal phenomenon in civil aircraft cabins, especially in some short-haul continental flights. It is necessary to develop an easy way to predict the thermal sensation of passengers and to direct the crew to control ECS. Due to the assessment consistency of the corrected PMV model and the adaptive model, the adaptive model of thermal neutrality temperature can be used as a method to predict the cabin optimal operative temperature. Because only the mean outdoor effective temperature ET* of a departure city is an input variable for the adaptive model, this method can be easily understood and implemented by the crew and can satisfy 80–90% of the thermal acceptability levels of passengers.     

风力机标模非定常数值模拟中的影响因素研究

基于自主研发的“亚跨超 CFD 软件平台”(TRIP3.0),采用刚性运动网格技术和动态拼接网格技术,开发了针对旋转类机械的非定常求解模块。本文开展了 NREL Phase VI 风力机标模非定常数值模拟中的影响因素研究,影响因素主要包括不同时间步长的影响、不同湍流模型的影响、刚性动网格技术和动态拼接网格技术的影响三个方面。本文数值模拟采用的控制方程为雷诺平均 N-S 方程,采用有限体积法离散控制方程,离散方程的时间方向采用“双时间步”方法求解,空间方向无粘项离散采用 MUSCL-Roe 格式,湍流模型采用 SA 和 SST 湍流模型,并引入多重网格和并行计算技术加速求解。数值模拟结果表明：时间步长、湍流模型、网格方案等因素主要影响风力机叶片吸力面的流动结构,进而影响吸力面的压力分布,而对压力面的流动结构和压力分布基本没有影响;采用刚性运动网格结合 SA 湍流模型所得到的压力分布更接近实验值。     

Bayesian uncertainty analysis of SA turbulence model for supersonic jet interaction simulations

The Reynolds Averaged Navier-Stokes(RANS) models are still the workhorse in current engineering applications due to its high efficiency and robustness. However, the closure coefficients of RANS turbulence models are determined by model builders according to some simple fundamental flows, and the suggested values may not be applicable to complex flows, especially supersonic jet interaction flow. In this work, the Bayesian method is employed to recalibrate the closure coefficients of Spalart-Allma...     

Uncertainty analysis of turbulence model in capturing flows involving laminarization and retransition

Flows experiencing laminarization and retransition are universal and crucial in many engineering applications. The objective of this study is to conduct an uncertainty quantification and sensitivity analysis of turbulence model closure coefficients in capturing laminarization and retransition for a rapidly contracting channel flow. Specifically, two commonly used turbulence models are considered: the Spalart-Allmaras (SA) one-equation model and the Menter Shear Stress Transport (SST) two-equation model. Thereby, a series of steady Reynolds Averaged Navier-Stokes (RANS) predictions of aero-engine intake acceleration scenarios are carried out with the purposely designed turbulence model closure coefficients. As a result, both SA and SST models fail to capture the retransition phenomenon though they achieve pretty good performance in laminarization. Using the non-intrusive polynomial chaos method, solution uncertainties in velocity, pressure, and surface friction are quantified and analyzed, which reveals that the SST model possesses much great uncertainty in the non-laminar regime, especially for the logarithmic law prediction. Besides, a sensitivity analysis is performed to identify the critical contributors to the solution uncertainty, and then the correlations between the closure coefficients and the deviations of the outputs of interest are obtained via the linear regression method. The results indicate that the diffusion-related constants are the dominant uncertainty contributors for both SA and SST models. Furthermore, the remarkably strong correlation between the critical closure coefficients and the outputs might be a good guide to recalibrate and even optimize the commonly used turbulence models.     

基于RANS-LES混合方法的翼型大迎角非定常分离流动研究

使用雷诺平均Navier-Stokes方程-大涡模拟（RANS-LES）混合方法中的延迟分离涡模拟（DDES）方法,模拟了NACA 0015翼型在大迎角下的静态绕流和强迫振荡运动并与实验值进行了比较。在大迎角静态翼型大分离流动模拟中,DDES方法捕获了非定常RANS计算未能获得的机翼背风面的涡脱落现象。在所采用的RANS和DDES模型中,基于剪切应力输运（SST）湍流模型的SST-DDES混合方法给出的时均压力系数分布与实验吻合得最好。在大迎角强迫振荡翼型绕流模拟中,DDES方法得到的非定常气动载荷与实验值吻合得很好,正确地反映了最大迎角处阻力和俯仰力矩的阶跃性突变,而非定常RANS计算则给出了完全错误的趋势。     

超声速湍流流场的RANS/LES混合计算方法研究

采用对接/拼接网格技术,建立了基于分区混合和基于湍流尺度混合的双重RANS/LES混合计算模型,并对环翼低速绕流、翼型跨声速绕流和球锥带凹窗外形二维超声速绕流进行了初步的数值模拟.环翼和翼型绕流计算表明,该混合模型可给出较合理的湍流宏观平均量;球锥带凹窗外形二维超声速绕流计算表明,该混合模型可得到超声速瞬态湍流脉动流场,凹窗处存在复杂的旋涡结构和波系结构,呈现较大尺度的脉动.但该模型还需要进一步的考核验证.     

跨声速机翼抖振初始迎角N-S方程定常计算分析

 应用代数法和椭圆型方程优化相结合的方法生成翼身组合体块结构网格。采用有限体积空间离散法和五步Runge-Kutta显式时间推进法求解N-S方程。基于雷诺平均N-S（RANS）方程,选用Spalart-Allmaras（SA）一方程模型模拟紊流。根据N-S方程定常计算结果,采用升力曲线、俯仰力矩曲线、后缘压力发散、跨声速激波位置以及机翼表面极限流线等几种判据,对跨声速机翼的抖振初始迎角进行了合理的预测分析。     

Progress and future prospects of CFD in aerospace—Wind tunnel and beyond

A historical perspective of computational fluid dynamics (CFD) in aerospace in the last 30 years is firstly given. It is shown that there still remain a number of problems that are geometrically simple but difficult to simulate even after many simulations were conducted over complex body configurations. The fact indicates that CFD research is now in the “specific phase” and requires some innovation.The innovation includes “evolutionary effort” and “revolutionary effort”. As an example of evolutionary effort, large eddy simulations/ Reynolds-averaged Navier–Stokes simulations (LES/RANS) hybrid method and its application examples are presented. A shift from RANS to LES/RANS hybrid method occurs not because of the advancement of computers but because of our recognition that separated flows are inherently unsteady and successful simulations require LES-like computations.Comment is given that there may be other types of research necessary to make CFD a real useful tool for a design in addition to simply showing CFD capability for complex body configurations. As one of the examples, construction of a CFD database is presented. Another issue is to make CFD infrastructures so that people outside CFD community may use CFD as a tool to formulate or refine their ideas.To find out revolutionary effort, the message given by Prof. Dean Chapman in 1977 is referred. Observation of current CFD research reveals that evaluation methods of “scale effect” that were believed to be the most important benefit of CFD have not yet been established. Such establishment is the key for the revolution of CFD and researchers need to focus their effort on the development of technologies to evaluate scale effect. Only with such new CFD technologies can “conceptual design with CFD” become feasible.     

Navier–Stokes analysis methods for turbulent jet flows with application to aircraft exhaust nozzles

This article presents the current status of computational fluid dynamics (CFD) methods as applied to the simulation of turbulent jet flowfields issuing from aircraft engine exhaust nozzles. For many years, Reynolds-averaged Navier–Stokes (RANS) methods have been used routinely to calculate such flows, including very complex nozzle configurations. RANS methods replace all turbulent fluid dynamic effects with a turbulence model. Such turbulence models have limitations for jets with significant three-dimensionality, compressibility, and high temperature streams. In contrast to the RANS approach, direct numerical simulation (DNS) methods calculate the entire turbulent energy spectrum by resolving all turbulent motion down to the Kolmogorov scale. Although this avoids the limitations associated with turbulence modeling, DNS methods will remain computationally impractical in the foreseeable future for all but the simplest configurations. Large-Eddy simulation (LES) methods, which directly calculate the large-scale turbulent structures and reserve modeling only for the smallest scales, have been pursued in recent years and may offer the best prospects for improving the fidelity of turbulent jet flow simulations. A related approach is the group of hybrid RANS/LES methods, where RANS is used to model the small-scale turbulence in wall boundary layers and LES is utilized in regions dominated by the large-scale jet mixing. The advantages, limitations, and applicability of each approach are discussed and recommendations for further research are presented.     

SA一方程湍流模型参数影响分析与辨识

SA(Spalart-Allmaras)一方程湍流模型是目前工程湍流计算中主要采用的湍流模型之一。首先,针对某典型战斗机的小攻角、中等攻角、大攻角流动工况,利用均匀试验设计方法分析SA一方程模型中8个参数取值对上述工况下飞机升力和阻力系数计算结果的影响规律;然后,建立工程湍流模型参数的辨识方法,并将其用于该战斗机大攻角工况下湍流模型参数cb1值的辨识调整。结果表明:不同工况下,湍流模型参数对计算结果的影响规律不同;在附着流状态下,对升力和阻力影响较大的参数是cv1和cb1;在中等攻角和较大攻角下,对升力和阻力影响较大的参数是cb1;适当减小参数cb1的取值后,升力和阻力系数的计算结果有较明显的改善,这可能与飞机大攻角分离流场中涡粘系数和剪切应力的发展与自由剪切流存在一定差异有关。