Criterion for Spanwise Spacing of Stall Cells

Groß, Andreas; Fasel, Hermann F.; Gaster, M.

doi:10.2514/1.j053347

Cited by 20 publications

(41 citation statements)

References 8 publications

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“…Gross et al [5] developed a theoretical model for the prediction of stall-cell spacing, which supported the linear relationship between the number of stall cells and aerofoil AR found in [3]. This model also predicts that stall cells are formed with a negative gradient of lift coefficient (CL) versus angle of attack (AoA), which was further verified recently by Manni et al [6] in a series of unsteady RANS simulations.…”

Section: Influential Factors Of Stall Cell Formationmentioning

confidence: 56%

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Numerical analysis on the oscillation of stall cells over a NACA 0012 aerofoil

Liu

Nishino

2018

Computers & Fluids

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A series of three-dimensional unsteady Reynolds-averaged Navier-Stokes (RANS) simulations are conducted to investigate the formation and oscillation of stall cells over a NACA 0012 aerofoil. The simulations are conducted with various physical and numerical conditions, such as the Reynolds number, angle of attack, chord-to-span ratio and span-wise mesh resolution. Results show a clear relationship between the oscillation of stall cells and the fluctuation of lift (observed between 17 and 19.5 degrees angle of attack at a high chord Reynolds number of one million). This unsteadiness shows some dependency on the span-wise mesh resolution; it is significant with a medium span-wise mesh resolution (corresponding to 10% of the chord) and moderate with finer resolutions (corresponding to 5% and 2.5% of the chord, respectively). In addition, a proper orthogonal decomposition (POD) method is adopted to further analyse the oscillatory characteristics of stall cells. In particular, it is shown that the first few POD modes have clear spatial patterns corresponding to the profile of stall cells and their time coefficients are correlated with the fluctuation of lift, further confirming the correlation between the stall cell oscillations and the lift fluctuation.

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Section: Influential Factors Of Stall Cell Formationmentioning

confidence: 56%

“…The air density is 1.225 kg/m 3 , and the viscosity is 1.7894 ×10 -5 kg/(m•s). The freestream velocity U∞ is set as 1.97 m/s and 14.607 m/s, respectively, for two different chord Reynolds number cases, Re = 1.35×10 5 and Re = 1×10 6 . A Cartesian coordinate system (x, y, z) is employed to describe the local coordinate, i.e.…”

Section: Flow Configurationsmentioning

confidence: 99%

Numerical analysis on the oscillation of stall cells over a NACA 0012 aerofoil

Liu

Nishino

2018

Computers & Fluids

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“…Based on this model, stall cells result from an instability that grows when the lift versus incidence slope is negative. Gross et al [45] proposed a model based on lifting line theory for the wavelength of the cells with respect to the slope of the C L α curve. Weihs and Katz [46] tried to explain the stall cells based on the Crow instability [47] and Rodriguez and Theofilis [48] linked stall cells formation to the appearance of a global unstable mode.…”

Section: Introductionmentioning

confidence: 99%

Similitude between 3D cellular patterns in transonic buffet and subsonic stall

Plante¹,

Dandois²,

Laurendeau

2019

AIAA Scitech 2019 Forum

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This paper studies the similitude between the 3D cellular patterns which appears in the simulation of transonic buffet and subsonic stall phenomenon using RANS/URANS simulations. These wings are obtained from the extrusion of a 2D airfoil with an added sweep angle and periodic boundary conditions imposed at both ends. This numerical setup allows to study three-dimensional buffet on the simplest configuration possible. Numerical solutions exhibit three-dimensional flows in the form of buffet cells. The latter are convected towards the wing tip when a sweep angle is added leading to the superposition of two frequencies. The first one is independent of the sweep angle and is characteristic of two-dimensional buffet. The second one increases with the sweep angle and is related to the convection of the buffet cells. These cells are reminiscent of the stall cells which are well-known but for low speed flow conditions. Solutions of the URANS equations for infinite swept wings in stall conditions at low speed are computed showing the same convection of the cellular patterns. These results lead us to think the discrepancies between 2D and 3D buffet are caused by the appearance of stall cells, which are the same as buffet cells, and not from a modification of the shock wave boundary layer interaction.

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“…Weihs and Katz [41] ascribed the phenomenon to the Crow instability [42] while Disotell and Gregory [43] claimed that stall cell formation could be related to shear layer instability. A more convincing theory was recently proposed separately by Sparlart [44] and Gross et al [45], who analyzed the stall cell formation based on the lifting line theory. They concluded that for a massively stalled aerofoil, locally reduced circulation could be found on the suction side, arranged alternatively with normal circulation induced by flow separation.…”

Section: Discussionmentioning

confidence: 99%

“…The relationship between stall cell formation and LEV, as well as the impact of the reduced frequency, is worth further investigation in future work. separately by Sparlart [44] and Gross et al [45], who analyzed the stall cell formation based on the lifting line theory. They concluded that for a massively stalled aerofoil, locally reduced circulation could be found on the suction side, arranged alternatively with normal circulation induced by flow separation.…”

Section: Discussionmentioning

confidence: 99%

Unsteady RANS Simulations of Strong and Weak 3D Stall Cells on a 2D Pitching Aerofoil

Liu

Nishino

2019

Fluids

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A series of three-dimensional unsteady Reynolds-averaged Navier–Stokes (RANS) simulations are conducted to investigate the formation of stall cells over a pitching NACA 0012 aerofoil. Periodic boundary conditions are applied to the spanwise ends of the computational domain. Several different pitching ranges and frequencies are adopted. The influence of the pitching range and frequency on the lift coefficient (CL) hysteresis loop and the development of leading-edge vortex (LEV) agrees with earlier studies in the literature. Depending on pitching range and frequency, the flow structures on the suction side of the aerofoil can be categorized into three types: (i) strong oscillatory stall cells resembling what are often observed on a static aerofoil; (ii) weak stall cells which are smaller in size and less oscillatory; and (iii) no stall cells at all (i.e., flow remains two-dimensional) or only very weak oval-shaped structures that have little impact on CL. A clear difference in CL during the flow reattachment stage is observed between the cases with strong stall cells and with weak stall cells. For the cases with strong stall cells, arch-shaped flow structures are observed above the aerofoil. They resemble the Π-shaped vortices often observed over a pitching finite aspect ratio wing.

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Criterion for Spanwise Spacing of Stall Cells

Cited by 20 publications

References 8 publications

Numerical analysis on the oscillation of stall cells over a NACA 0012 aerofoil

Numerical analysis on the oscillation of stall cells over a NACA 0012 aerofoil

Similitude between 3D cellular patterns in transonic buffet and subsonic stall

Unsteady RANS Simulations of Strong and Weak 3D Stall Cells on a 2D Pitching Aerofoil

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