Computational and Experimental Investigation of a Nonslender Delta Wing

Gordnier, Raymond E.; Visbal, Miguel R.; Gursul, Ismet; Wang, Zhijin

doi:10.2514/1.37848

Cited by 26 publications

(3 citation statements)

References 33 publications

(57 reference statements)

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“…We do not take into account the effects of the enhanced turbulent mixing and boundary layer effects at higher Reynolds numbers. However, the LEV has been found to be very resilient to the effects of Reynolds numbers [23]. Therefore, while this investigation does not provide a quantitative description of the full-scale flow, it enables the understanding of the key features of downwind sail flow.…”

Section: Overview Of the Present Workmentioning

confidence: 95%

The leading-edge vortex of yacht sails

Arredondo-Galeana

Viola

2018

Ocean Engineering

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It has been suggested that a stable Leading Edge Vortex (LEV) can be formed from the sharp leading edge of asymmetric spinnakers. If the LEV remains stably attached to the leading edge, it provides an increase in the thrust force. Until now, however, the existence of a stable and attached LEV has only been shown by numerical simulations. In the present work we experimentally verify, for the first time, that a stable LEV can be formed on an asymmetric spinnaker. We tested a 3D printed rigid sail in a water flume at a chord-based Reynolds number of ca. 104 . The sail was tested in isolation (no hull and rigging) at an incidence with the flow equivalent to an apparent wind angle of 55• and a heel angle of 10 • . The flow field was measured with particle image velocimetry over horizontal cross sections. We found that on the leeward side of the sail, the flow separates at the leading edge reattaching further downstream and forming a stable LEV. The LEV grows in diameter from the root to the tip of the sail, where it merges with the tip vortex. We detected the LEV using the γ 1 and γ 2 criteria, and we verified its stability over time. The lift contribution provided by the LEV was computed solving a complex potential model of each sail section. This analysis showed that the LEV provides more than 10% of the total sail's lift. These findings suggests that the performance of asymmetric spinnakers could be significantly enhanced by promoting a stable LEV.

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Section: Overview Of the Present Workmentioning

confidence: 95%

The leading-edge vortex of yacht sails

Arredondo-Galeana

Viola

2018

Ocean Engineering

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“…For the same wing model at the same incidence angle, Hahn and Drikakis ( 9 , 10 ) found that an implicit large eddy simulation is more accurate than hybrid RANS/LES at the region close to the wing tip, but some features of the flow are still different from the experimental data. By combining computational and experimental work, Gordnier et al ( 11 ) examine the flow structures over a 50-deg-swept plane delta wing at 15°. Further computations are still needed to fully understand transitional or turbulent flow.…”

Section: 0 Introductionmentioning

confidence: 99%

Experimental investigation of the flow structures over a 40° swept wing

Zhang

Jaworski²,

McParlin

et al. 2019

Aeronaut. j.

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Flow over a moderately swept wing is characterised by complex localised flow vortex topologies such as ‘closed’ separation bubbles or ‘open’ separation structures. A model of a complex cambered, twisted, tapered wing with 40° leading edge sweep, representative of those designed for manoeuvre at high subsonic Mach numbers, was investigated using the oil-film visualisation, stereo particle image velocimetry and force moment measurements. Wind-tunnel tests were conducted at a range of Reynolds number from 2.1×105 to 8.4×105 and at angles of incidence from −1° to 22°. Still images combined with video clips enable flow patterns over the wing model to be interpreted more clearly and accurately. Using successive images extracted from the video of flow visualisation, the movement of the oil pigment has been estimated. The influence of the Reynolds number and incidence angle was discussed through analysing the flow pattern over the wing surface. Additionally, the link between the flow structures present and the wing aerodynamic performance was studied.

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“…Computations of the flow structure on delta wings of low sweep angle, with emphasis on lower values of Reynolds number, have been performed by Gordnier and Visbal [21] using a high-order, structured-grid, finite difference algorithm [22]. Gordnier and Visbal [23] and Gordnier et al [24] have also addressed features of the flow structure of planar delta wings at moderate values of Reynolds number.…”

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confidence: 99%

1303 Unmanned Ccombat Air Vehicle Flowfield Simulations and Comparison with Experimental Data

Sherer¹,

Visbal²,

Gordnier³

et al. 2011

Journal of Aircraft

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In this work, high-order computations of the flowfield around a 1303 unmanned combat air vehicle configuration are performed and compared with recently collected experimental data obtained at Lehigh University. The computational approach used a high-order overset-grid flow solver developed in the Air Vehicles Directorate of the U.S. Air Force Research Laboratory that employs up-to-sixth-order compact finite differences and high-order, low-pass numerical filters to accurately resolve detailed flow features in a robust manner. The experimental data was collected via a particle image velocimetry technique in a free-surface water channel. Both quantitative and qualitative comparisons between computational and experimental results are done at a plane located at eight-tenths of the half-span for various Reynolds numbers and angles of attack, with the results comparing quite favorably for most flow conditions. Computational images of the flowfield are used to elucidate angle of attack and Reynolds number effects on this configuration, as well as to investigate the formation and evolution of the leading-edge and centerbody vortical structures and the impact that angle of attack has on their formation mechanisms. Nomenclature a, b = explicit compact differencing coefficients C root = wing root chord C = local wing chord at given spanwise locationviscous vector fluxes f i = explicit compact filter coefficients I = identity matrix I p , J p , K p = computational indices of interpolation donor point J = Jacobian of the coordinate transformation L mac = mean aerodynamic chord L ref = reference length (L ref L mac ) M = Mach number Pr = Prandtl number, 0.72 for air p = nondimensional static pressure Q = vector of dependent variables Re = reference Reynolds number, 1 u 1 L ref = 1 Re C root = reference Reynolds number based on wing root chord, 1 u 1 C root = 1 Re mac = reference Reynolds number based on mean aerodynamic chord, 1 u 1 L mac = 1 R , R , R = Laplace interpolation coefficients in , , and directions S = wing semispan T = nondimensional static temperature t = nondimensional time U, V, W = contravariant velocity components U 1 = freestream velocity u, v, w = nondimensional Cartesian velocity components in the x, y, and z directions u 1 , u 2 , u 3 = u, v, w hVi = time-averaged velocity vector x, y, z = nondimensional Cartesian coordinates in streamwise, normal, and spanwise directions based on wing orientation (nondimensionalized by the mean aerodynamic chord, L mac ) x LE = x coordinate of the local leading edge as measured from the apex x 1 , x 2 , x 3 = x, y, z x = nondimensional chordwise distance from the local leading edge, x x LE =C x root = nondimensional chordwise distance from the apex, x=C root = angle of attack f = implicit compact filter coefficient = implicit compact differencing coefficient = specific heat ratio, 1.4 for air , , = interpolation offsets in the , , and directions ij = Kronecker delta function 2 , 2 , 2 = second-order finite difference operators in , , 6 , 6 , 6 = sixth-order finite differe...

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Computational and Experimental Investigation of a Nonslender Delta Wing

Cited by 26 publications

References 33 publications

The leading-edge vortex of yacht sails

The leading-edge vortex of yacht sails

Experimental investigation of the flow structures over a 40° swept wing

1303 Unmanned Ccombat Air Vehicle Flowfield Simulations and Comparison with Experimental Data

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