Unsteady Wake Flow Analysis of an Aircraft under low-speed Stall Conditions using DES and PIV

Waldmann, Andreas

doi:10.2514/6.2015-1096

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…The mesh was built up this way consciously to prevent difficulties with the transition of cell types within the fuselage boundary layer, as observed in previous simulations [34]. With respect to modeling the influence of the separated flow on the surface pressure in this domain, the present DDES results, however, are still superior compared to URANS results, as discussed by Waldmann et al [38]. The DDES predicted and the measured pressure-side data match very well at all sections; compare to Fig.…”

Section: A Forces and Wing Pressure Distributionssupporting

confidence: 35%

Prediction and Measurement of the Common Research Model Wake at Stall Conditions

Lutz

Gansel

Waldmann

et al. 2016

Journal of Aircraft

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The development of the unsteady wake of transport aircraft under stall conditions and its impact on the empennage are challenging to predict, and the flow physics is far from being understood. In the European Strategic Wind Tunnels Improved Research Potential project, time-resolved particle image velocimetry measurements on the separated wake of the NASA Common Research Model were performed in the cryogenic European Transonic Windtunnel for flight Reynolds number conditions supplemented by aerodynamic measurements for a great variety of inflow conditions. In the time-resolved particle image velocimetry measurements, both low-speed stall (M ∞ 0.25, Re 11.6∕17 million) and high-speed stall conditions (M ∞ 0.85, Re 19.8∕30 million) were considered and the frequency resolution was as high as 1 kHz, enabling a sufficient characterization of the turbulent wake spectrum. For selected high-and low-speed stall conditions, hybrid Reynolds-averaged Navier-Stokes/large-eddy simulations were performed. In the present paper, the numerical results are discussed and compared to the experiments and first evaluations of the particle image velocimetry data are presented. NomenclatureYoung modulus M ∞ = freestream Mach number q = dynamic pressure Re = Reynolds number based on the reference chord length S = wing reference area Sr = Strouhal number based on the reference chord length and freestream velocity t = time U = velocity U ∞ = freestream velocity x, y, z = Cartesian coordinates y = wall distance normalized by the viscous length scale α = angle of attack Δ = filter width in large-eddy simulations η = spanwise position normalized by the semispan of the wing ω = vorticity

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Section: A Forces and Wing Pressure Distributionssupporting

confidence: 35%

Prediction and Measurement of the Common Research Model Wake at Stall Conditions

Lutz

Gansel

Waldmann

et al. 2016

Journal of Aircraft

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“…We also plotted the pressure distributions at 28.3% spanwise position of the main wing in Fig. 10e, and confirmed good agreement among the two numerical solutions and the experimental data from [49]. In other words, it has been demonstrated that Post Limiter 3 properly detected dirty-cells and triggered the slope limiter at necessary places.…”

Section: Numerical Examplessupporting

confidence: 74%

Postlimiters and Simple Dirty-Cell Detection for Three-Dimensional Unstructured (Unlimited) Aerodynamic Simulations

et al. 2018

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“…The superiority of the hybrid RANS/LES approach over RANS in modeling the influence of the separated flow on the surface pressure is discussed in Waldmann, Gansel, Lutz and Krämer. 28 However, the present mesh was build up this way consciously to prevent difficulties with transition of cell types within the fuselage boundary layer as observed in previous simulations. 35 In contrast the pressure side data match very well at all stations.…”

Section: A Forces and Wing Pressure Distributionsmentioning

confidence: 99%

Time-resolved Prediction and Measurement of the Wake past the CRM at high Reynolds number stall conditions

Lutz

2015

53rd AIAA Aerospace Sciences Meeting

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The development of the unsteady wake of transport aircraft under stall conditions and its impact on the empennage is challenging to predict and the flow physics is far from being understood. In the European ESWI RP project time-resolved PIV (TR-PIV) measurements on the separated wake of the NASA Common Research Model (CRM) were performed in the cryogenic European Transonic Windtunnel (ETW) for flight Reynolds number conditions supplemented by aerodynamic measurements for a great variety of inflow conditions. In the TR-PIV measurements both, low-speed stall (M∞ = 0.25, Re = 11.6 / 16.5M) and high-speed stall (M∞ = 0.85, Re = 19.8 / 30M) were considered and the frequency resolution was as high as 1 kHz enabling a sufficient characterization of the turbulent wake spectrum. Further hybrid RANS/LES simulations were performed for selected low-and high-speed stall conditions. In the present paper the numerical results are discussed and compared to the experiments and first evaluations of the PIV data are presented.

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Unsteady Wake Flow Analysis of an Aircraft under low-speed Stall Conditions using DES and PIV

Cited by 4 publications

References 17 publications

Prediction and Measurement of the Common Research Model Wake at Stall Conditions

Prediction and Measurement of the Common Research Model Wake at Stall Conditions

Postlimiters and Simple Dirty-Cell Detection for Three-Dimensional Unstructured (Unlimited) Aerodynamic Simulations

Time-resolved Prediction and Measurement of the Wake past the CRM at high Reynolds number stall conditions

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