Stochastic aerodynamic analysis for compressor blades with manufacturing variability based on a mathematical dimensionality reduction method

Guo, Zhengtao; Chu, Wuli

doi:10.1177/09544062211062452

Cited by 11 publications

(5 citation statements)

References 38 publications

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“…When the total number of workpieces is large enough, the geometric deviation distribution based on the Gaussian process is in good agreement with the actual machining deviation measurement data. 16,26 Therefore, under the machining deviation uncertainty influence, this work considers that the thickness deviation value also obeys the Gaussian distribution. UQ analysis of the influence of thickness deviation on compressor performance under the 1st-level and the 3rd-level machining accuracy is carried out.…”

Section: Blade Model Construction Methodsmentioning

confidence: 99%

Mechanism analysis and uncertainty quantification of blade thickness deviation on rotor performance

Chu

Chen

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part A:

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The blade thickness distribution is an important geometric parameter of a compressor rotor blade. It determines the aerodynamic performance of a rotor, which should be carefully designed. However, the manufacturing inaccuracies cause the blade thickness distribution to deviate from the ideal design. These geometric deviations alter the flow field near the blade surface, which affects the aerodynamic performance of the rotor. Therefore, it is of great significance to quantitatively investigate the effects of blade thickness deviation on the aerodynamic performance. In this paper, the influence of blade thickness deviation on the flow field is analyzed based on a transonic compressor rotor, and an uncertainty quantification process is performed to study the effects of blade thickness deviation on the aerodynamic performance. Cases with different geometry features are checked in the current study using 3-dimensional Reynolds-averaged Navier–Stokes simulations. Results show that the blade thickness deviation leads to changes in the intensities of the expansion wave in the upper part of the blade suction and the passage shock wave, which affects the supercharging process of the rotor. The influence of thickness deviation on the strength of the tip leakage vortex changes the isentropic efficiency of the rotor. The results of the uncertainty quantitative analysis indicate that the linear correlation between the variation of rotor performance and the thickness deviation is strong when the machining accuracy is high, whereas the linear correlation between the two is weakened when the tolerance range is larger.

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Section: Blade Model Construction Methodsmentioning

confidence: 99%

Mechanism analysis and uncertainty quantification of blade thickness deviation on rotor performance

Chu

Chen

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part A:

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“…The calculation mesh in a single flow passage has about 165,000 cells, and Y+ is about 1.0. The mesh has been verified to meet the requirement of grid independence through previous work (Guo and Chu 2022), and used for many aerodynamic studies (Guo et al 2022a, b).…”

Section: Description Of the Numerical Modelmentioning

confidence: 99%

“…Gaussian distributions for flow variations have been widely applied in describing stochastic flow variations (Hosder et al 2007;Loeven et al 2007;Loeven and Bijl 2010). Because the disturbance range of uncertainty variables cannot be infinite, the truncated Gaussian distribution is more practical to describe the uncertainty, which has been accepted by many aerodynamic UQ studies (Wu et al 2017;Guo and Chu 2022). Thus, it is also employed to illustrate the variation of inlet incidences…”

Section: Evaluations Of Performance Impactmentioning

confidence: 99%

Effects of Inlet Incidence Perturbations on Compressor Cascade Performance using Adaptive Sparse Grid Collocation

2023

JAFM

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The effects of inflow variations due to the working environment and flight attitude changes on turbomachines are considerable in the real world. Nevertheless, uncertainty quantification can be adopted to assess mean performance changes and perform the aerodynamic shape design as well as optimization. Thus, an uncertainty quantification method of adaptive sparse grid collocation (ASGC) was first introduced to address the inflow uncertainties’ effect issue effectively and accurately. Then, ASGC was utilized to evaluate the impacts of inlet incidence perturbations at different perturbation scales and reference inflow Mach numbers on the aerodynamic performance of a controlled diffusion cascade. The results showed that compared with the Monte Carlo simulation and static sparse gird collocation, the statistical accuracy and response accuracy of ASGC were maintained, and meanwhile its model construction efficiency was significantly improved because of the nested adaptive sampling feature. Under the perturbations of inlet incidences with high reference incidences, the mean aerodynamic loss always aggravates. The changes in aerodynamic loss nonlinearly depend on the inlet incidence perturbations, and the nonlinear dependence becomes greater when the perturbation scale. expands. At the same perturbation scale, the nonlinear dependence on the inlet incidence perturbations is further enhanced when the reference inflow Mach number rises. Finally, uncertainty quantification of the flow field revealed that the fluctuation of flow accelerations at the leading edge plays a fundamental role in determining the uncertainty of the aerodynamic loss.

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“…The verification of the mesh-independence has been studied in the previous work. 29 The node number of the computing mesh is encrypted to about 1.65E05, in which the calculated Y + is about 1. Figure 1 gives the local computational mesh of the airfoil and the accuracy verification of the numerical scheme.…”

Section: Uncertainty Modeling Of Inflow and Geometric Variationsmentioning

confidence: 99%

“…The profile error defines the normal distance between the manufactured and design profile lines, which is related to the variation of maximum thickness and LE radius. The open literatures 29,31 have respectively shown that the maximum thickness and LE variations affect the boundary-layer development. The torsion error refers to the angular difference between the manufactured and design profiles.…”

Section: Uncertainty Modeling Of Inflow and Geometric Variationsmentioning

confidence: 99%

Uncertainty analysis of global and local performance impact of inflow and geometric uncertainties using sparse grid-based non-intrusive polynomial chaos

Guo

Chu

Zhang

2022

Proceedings of the Institution of Mechanical Engineers, Part A:

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Flow variations at the inlet boundary due to the compressor operational condition changes and geometric variations of the realistic compressor blades due to the manufacturing variability cannot be absolutely avoided, the global and local performance impact of which requires to be considered in the mechanism study of performance change and the aerodynamic shape design. In this paper, a method to analyze the simultaneous impact of the inflow Mach number, inlet incidence and geometric uncertainties was proposed. To make the uncertainty modeling of geometric variations faster and closer to engineering practice, a parametric mathematical model based on scanning points on the blade was introduced to describing the profile and torsion errors in the method specially. Meanwhile, a sparse grid based-Non-Intrusive Polynomial Chaos (NIPC) was used for uncertainty quantification and uncertainty sensitivity analysis to alleviate the computational burden. Then, the method was combined with a loss source calculation method to estimate the global and local aerodynamic loss changes of a controlled diffusion compressor blade in a reference flow state of high inflow Mach number and large positive incidence, and the response performance of sparse grid-based NIPC was verified. The results show that inlet incidence and torsion error have a significance uncertainty effect on the boundary-layer separation above the suction surface, which is main reason for the fluctuation of global aerodynamic loss. The uncertainty effect of profile error on the boundary-layer separation is relatively weak, but profile error could have a certain uncertainty effect on the leading edge separation. The boundary-layer separation is insensitive to Inflow Mach number. Furthermore, a stochastic aerodynamic analysis in different reference inflow states was investigated, which reveals some laws that the uncertainty of the aerodynamic losses and the sensitivity of the inflow and geometric uncertainties change with reference inflow states.

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Stochastic aerodynamic analysis for compressor blades with manufacturing variability based on a mathematical dimensionality reduction method

Cited by 11 publications

References 38 publications

Mechanism analysis and uncertainty quantification of blade thickness deviation on rotor performance

Mechanism analysis and uncertainty quantification of blade thickness deviation on rotor performance

Effects of Inlet Incidence Perturbations on Compressor Cascade Performance using Adaptive Sparse Grid Collocation

Uncertainty analysis of global and local performance impact of inflow and geometric uncertainties using sparse grid-based non-intrusive polynomial chaos

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