Experimental analysis of transonic buffet on a 3D swept wing using fast-response pressure-sensitive paint

Sugioka, Yosuke; Koike, Shunsuke; Nakakita, Kazuyuki; Numata, Daiju; Nonomura, Taku; Asai, Keisuke

doi:10.1007/s00348-018-2565-5

Cited by 75 publications

(39 citation statements)

References 31 publications

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“…The spanwise wavelength varied between 0.55 and 1.6 MAC. Sugioka et al (2018) performed a spectral analysis using unsteady PSP data on an 80 %-scaled NASA common research model. A convection speed of 0.53 U ∞ at St = 0.31 was reported at M = 0.85 and α = 4.68 • , which is 1.0 • above buffet onset.…”

Section: Shock Motion Analysismentioning

confidence: 99%

“…Early applications in transonic wind tunnels (Steimle, Karhoff & Schröder 2012;Merienne et al 2013) had poor resolution and restricted coverage, limited by the paint composition, its application, and camera technology. Having demonstrated the potential to clarify the flow mechanisms of complex flows, this rapidly evolving technique attracted attention, with recent experiments successfully acquiring unsteady pressure over the entire wing surface (Lawson, Greenwell & Quinn 2016;Sugioka et al 2018). In effect, rather than being confined to the discrete locations of pressure transducers, analysis is enabled over a much wider area, giving critical insight as discussed herein.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of a civil aircraft wing transonic shock buffet experiment

2019

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The physical mechanism governing the onset of transonic shock buffet on swept wings remains elusive, with no unequivocal description forthcoming despite over half a century of research. This paper elucidates the fundamental flow physics on a civil aircraft wing using an extensive experimental database from a transonic wind tunnel facility. The analysis covers a wide range of flow conditions at a Reynolds number of around 3.6 × 10 6 . Data at pre-buffet conditions and beyond onset are assessed for Mach numbers between 0.70 and 0.84. Critically, unsteady surface pressure data of high spatial and temporal resolution acquired by dynamic pressure-sensitive paint is analysed, in addition to conventional data from pressure transducers and a root strain gauge. We identify two distinct phenomena in shock buffet conditions. First, we highlight a low-frequency shock unsteadiness for Strouhal numbers between 0.05 and 0.15, based on mean aerodynamic chord and reference free stream velocity. This has a characteristic wavelength of approximately 0.8 semi-span lengths (equivalent to three mean aerodynamic chords). Such shock unsteadiness is already observed at low-incidence conditions, below the buffet onset defined by traditional indicators. This has the effect of propagating disturbances predominantly in the inboard direction, depending on localised separation, with a dimensionless convection speed of approximately 0.26 for a Strouhal number of 0.09. Second, we describe a broadband higher-frequency behaviour for Strouhal numbers between 0.2 and 0.5 with a wavelength of 0.2 to 0.3 semi-span lengths (0.6 to 1.2 mean aerodynamic chords). This outboard propagation is confined to the tip region, similar to previously reported buffet cells believed to constitute the shock buffet instability on conventional swept wings. Interestingly, a dimensionless outboard convection speed of approximately 0.26, coinciding with the low-frequency shock unsteadiness, is found to be nearly independent of frequency. We characterise these coexisting phenomena by use of signal processing tools and modal analysis of the dynamic pressure-sensitive paint data, specifically proper orthogonal and dynamic mode decomposition. The results are scrutinised within the context of a broader research effort, including numerical simulation, and viewed alongside other experiments. We anticipate our findings will help to clarify experimental and numerical observations in edge-of-the-envelope conditions and to ultimately inform buffet-control strategies.

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Section: Shock Motion Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of a civil aircraft wing transonic shock buffet experiment

2019

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“…The DLR-FlowSimulator python interface allows for the definition of 64 surface probes (see Fig. 6) placed at the location of the unsteady pressure transducers in the wind tunnel experiments [18,24,30]. C P is extracted every 5 timesteps resulting in an extraction frequency of 400 Hz, equivalent to a non-dimensional Strouhal number, St = fc mac /U ∞ , of 9.5; sufficient to collect 20 samples per period of oscillation at highest expected frequency based on previous experimental observations.…”

Section: Global Forces and Surface Samplingmentioning

confidence: 99%

“…Towards wing root and over the fuselage the fluctuations are negligible. [18,24] and NASA [30] plus additional ones included in CFD Time-accurate C P is not reported herein, however an animation is provided as supplementary material. It shows that the shock oscillates on the wing surface in a sinusoidal manner.…”

Section: Shock-buffet Dynamicsmentioning

confidence: 99%

“…Experimental campaigns of National Aeronautics and Space Administration (NASA) [29,30] provide the base for validation of current results, including the decision on flight conditions. The observations from Japan Aerospace Exploration Agency (JAXA) wind tunnel campaigns [18,24] are used for qualitative comparison, since the difference in flight Re and wind tunnel far field dynamic pressure resulted in different wing deformations, making a quantitative comparison not possible [31].…”

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confidence: 99%

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Unsteady shock front waviness in shock-buffet of transonic aircraft

Apetrei

Ciobaca²,

Curiel-Sosa

et al. 2020

Adv. Aerodyn.

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The unsteady transonic aerodynamics of a wing-body configuration is investigated by solving the Unsteady Reynolds-averaged Navier-Stokes equations closed with the full Reynolds Stress Model. This work presents the prediction of flow field characteristics during deep shock-buffet penetration of a transport aircraftrepresentative geometry. Mach number of 0.85, and Reynolds number of 5 million based on the mean chord, are selected to reproduce experimental test conditions that serve as validating datasets. The results obtained give information about both surface and flow field shock-buffet dynamics. An unsteady shock front is observed on the suction side of the wing which gives birth to the so-called buffet cells. Flow field characteristics are dominated by the presence of lambda-shaped shocks and fully separated boundary layer over a significant part of the wing.

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