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Bridging tunnel and CFD for V-tail ruddervators: resolving wall-interference bias and establishing ruddervator effectiveness

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Abstract

V-tail empennages promise lower wetted area and junction drag than conventional tails, but their control power in the low Reynolds number regime relevant to small unmanned aerial vehicles (UAVs) remains weakly quantified. This study measures and predicts the lift-curve slope and the plain-flap (ruddervator) effectiveness of a subscale V-tail across five deflection settings (minus 30, minus 15, zero, plus 15, and plus 30°) and angles of attack from zero to 15°. A coordinated campaign combined low-speed wind tunnel testing using a three-component balance with Reynolds-matched computational fluid dynamics (CFD) using steady Reynolds-averaged Navier–Stokes with a realizable two-equation turbulence closure in a domain that replicated the tunnel test section. The key metrics extracted were the lift-curve slope, the ruddervator effectiveness, and the drag polars; these results were placed on the ESDU 74011 carpet plots for full-span plain controls. The computational predictions produced smooth, monotonic lift curves and a ruddervator effectiveness of approximately 0.29 per radian for the V-tail geometry and approximately 0.34 per radian for a planar reference variant—values that fall within the ESDU bands—while the wind tunnel under-predicted the ruddervator effectiveness and exhibited signatures of wall interference and small incidence offsets at large flap deflections. These discrepancies are attributed to blockage and wall-proximity effects rather than deficiencies in the control concept. For UAV designers, the findings indicate that V-tails with flap-to-chord ratios of 0.30–0.35 and adequate effective aspect ratio can deliver control effectiveness comparable to conventional tails of similar projected volume, with potential drag savings and manageable control mixing handled in software. Practical guidance is provided for test-section selection, wall and blocked-flow corrections, and data-reduction practices to obtain unbiased slopes in future campaigns.
Original languageEnglish
Article number2693173
JournalMechanics Based Design of Structures and Machines
Volume54
Issue number1
DOIs
Publication statusPublished - 10 Jul 2026

Keywords

  • Computational dynamics
  • boundary element methods
  • dynamics of machines

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