Flutter prediction in turbomachinery with energy method

Zhang, X W; Wang, Y R; Xu, Kang

doi:10.1177/0954410011405942

Cited by 13 publications

(8 citation statements)

References 25 publications

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“…Meanwhile, the investigation of turbulence model for transonic fan focused on the steady analysis in the past. Mostly, the effects of turbulence model on flutter prediction have not been researched [8][9][10][11] .…”

Section: Introductionmentioning

confidence: 98%

Effects of Turbulence Model on Flutter Prediction of a Transonic Fan

Zhang

Wang

et al. 2016

AIAA Modeling and Simulation Technologies Conference

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Four different turbulence models have been employed to investigate the aeroelastic stability of NASA Rotor 67 and a transonic fan by use of the energy method. Firstly, the amplitude and phase of the first harmonic pressure on blade surface have been analyzed. Then the characteristics of flutter at different working points and nodal diameters have been investigated. Finally, the flutter boundary of the fan has been predicted and compared to the measured one. The simulation results for the steady characteristics by use of k-ε model and k-ω model agree better with the test data than those of the SST model and RNG k-ε model. The aerodynamic damping predicted by use of these models are approximately the same at the peak efficiency point. However, compared to the test data, the aerodynamic damping calculated by use of SST model are more conservative than k-ε model at the near-stall point. Therefore, the k-ε model is more suitable to flutter prediction of transonic fans. Nomenclature1B = first bending 1T = first torsion C = damping matrix c = blade chord length, m d k = the k-th vibration displacement vector E = Young's modulus, GPa F a = aerodynamic load matrix K = stiffness matrix M = mass matrix N = number of blade n  = surface unit normal vector p = pressure, Pa PS = pressure surface q cfd = modal amplitude q k = generalized displacement of the k-th modal S = area of blade surface, m 2 Span = height of the blade SS = suction surface T = vibrating period of the blade, s t = time, s v  = vibrating velocity of the blade 2 W aero = aerowork, J x= structural displacement vector y + = dimensionless normal distance from the wall φ k = the k-th modal shape vector λ k = the k-th eigenvalue of system μ = Poisson's ratio ρ = density, kg/m 3 σ = interblade phase angle ω k = the k-th natural angular frequency of the blade, rad/s ζ aero = aerodynamic modal damping ratio

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Section: Introductionmentioning

confidence: 98%

Effects of Turbulence Model on Flutter Prediction of a Transonic Fan

Zhang

Wang

et al. 2016

AIAA Modeling and Simulation Technologies Conference

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“…Because of the reduction of computational costs time, the flutter prediction of compressor blades was developed rapidly with the increasing accuracy and efficiency. Most results were present by the aerodynamic work or damping with different interblade phase angles to judge the flutter [2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Sensitive Flutter Parameters Analysis with Respect to Flutter-free Design of Compressor Blade

Hai¹,

Lin²,

Li³

2015

Procedia Engineering

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As the mission requirements of the aero engine improve, the blade aerodynamic loading is higher, especially for lightweight designed blade. The possibility of the blade self-excited vibration increases, so flutter becomes one of the problems for fan and compressor design. However, there is no flutter related parameters in engineering as a reference for compressor flutter-free design until now. That is why the sensitive flutter parameters were studied which could suppress the flutter. Nomenclature W aerodynamic work A blade surface area T, t time V positive direction of blade oscillation n positive direction of pressure P pressure of blade surface

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“…response from aerodynamic exciting sources and negative aerodynamic damping, i.e., flutter [5][6][7][8], many types of friction dampers have been studied and applied in actual structures. Among them, the under-platform damper has been extensively studied in detail [9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Prediction Method for the Damping Effect of Ring Dampers Applied to Thin-Walled Gears Based on Energy Method

Wang

Jiang

et al. 2018

Symmetry

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In turbomachinery applications, thin-walled gears are cyclic symmetric structures and often subject to dynamic meshing loading which may result in high cycle fatigue (HCF) of the thin-walled gear. To avoid HCF failure, ring dampers are designed for gears to increase damping and reduce resonance amplitude. Ring dampers are installed in the groove. They are held in contact with the groove by normal pressure generated by interference or centrifugal force. Vibration energy is attenuated (converted to heat) by frictional force on the contact interface when the relative motion between ring dampers and gears takes place. In this article, a numerical method for the prediction of friction damping in thin-walled gears with ring dampers is proposed. The nonlinear damping due to the friction is expressed as equivalent mechanical damping in the form of vibration stress dependence. This method avoids the forced response analysis of nonlinear structures, thereby significantly reducing the time required for calculation. The validity of this numerical method is examined by a comparison with literature data. The method is applied to a thin-walled gear with a ring damper and the effect of design parameters on friction damping is studied. It is shown that the rotating speed, geometric size of ring dampers and friction coefficient significantly influence the damping performance.

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Flutter prediction in turbomachinery with energy method

Cited by 13 publications

References 25 publications

Effects of Turbulence Model on Flutter Prediction of a Transonic Fan

Effects of Turbulence Model on Flutter Prediction of a Transonic Fan

Sensitive Flutter Parameters Analysis with Respect to Flutter-free Design of Compressor Blade

A Prediction Method for the Damping Effect of Ring Dampers Applied to Thin-Walled Gears Based on Energy Method

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