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Comparative aerodynamic performance assessment of NACA 2412 and NACA 0012 aerofoils with winglet integration: a computational study using MATLAB-CATIA-CFD framework

Sep 2026 · Discover Vehicles · Vol 2 · 0 citations · 81 references

Abstract

Winglets are aerodynamic devices that reduce induced drag by mitigating wingtip vortices, thereby improving aircraft fuel efficiency and overall performance. This study presents a comparative computational investigation of the aerodynamic performance of wings with NACA 2412 (cambered) and NACA 0012 (symmetric) airfoils, with and without winglets. The methodology integrates CATIA for geometric modeling, MATLAB for preliminary aerodynamic analysis, and ANSYS Fluent for detailed computational fluid dynamics (CFD) simulations at Reynolds number Re = 1.5 × 10⁶ and angles of attack α = 0–16°. Quantitative validation against published experimental data shows maximum deviations of 3.1% for the lift coefficient and 2.9% for the drag coefficient. Mesh independence was verified with y⁺ < 1 and an element count of 2.8 × 10⁶. Under the specific conditions studied, winglet integration increased the lift-to-drag (L/D) ratio by 13.5–16.8% for NACA 2412 and 12.9–16.2% for NACA 0012 at moderate angles of attack (4–8°). Quantitative vortex analysis using the Q-criterion and λ₂ methods revealed that winglets reduce vortex intensity primarily by increasing the core radius (15.6% for NACA 2412, 14.3% for NACA 0012) rather than simply reducing vorticity magnitude. The cambered NACA 2412 consistently generated higher absolute lift (approximately 13–15% higher CL) than the symmetric NACA 0012, though the winglet configuration reduced the performance gap. These findings demonstrate that winglet effectiveness is aerofoil-dependent, with each aerofoil type achieving optimal performance at a different angle of attack. The study provides quantitative performance benchmarks for future optimization studies, though the results are limited by the specific geometric and flow conditions examined. The validated computational framework establishes a foundation for future design optimization, including studies of winglet geometry variation and structural integration.

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