A study on the Reynolds effect on Aerodynamic Scaling of a Small Flying Wing Aircraft

João Miguel Carvalho Dias

Key information

Authors:

João Miguel Carvalho Dias (João Miguel Carvalho Dias)

Supervisors:

Afzal Suleman (Afzal Suleman); Fernando José Parracho Lau (Fernando José Parracho Lau)

Published in

July 9, 2026

Abstract

Geometric scaling of aircraft models inevitably alters the chord-based Reynolds number, modifying boundary layer development, transition behaviour, and ultimately the aerodynamic performance of the scaled model relative to the full-size configuration. This work investigates the Reynolds number effects on aerodynamic scaling of the X56-1311 aerofoil, extracted from the X-56 NASA MUTT flying wing, across six geometric scales in the incompressible, low-to-moderate Reynolds number regime where transitional phenomena are significant. Two-dimensional Computational Fluid Dynamics (CFD) simulations are conducted in SU2 using the Spalart-Allmaras (SA) turbulence model coupled with the Bas-Cakmakcioglu (B-C) transition model across multiple angles of attack. Under Free Reynolds conditions, where flow conditions are held constant and the Reynolds number varies with chord length, drag coefficient deviations dominate the scaling error, reaching 16.46% at the smallest scale driven primarily by the formation of Laminar Separation Bubbles (LSBs) at reduced Reynolds numbers, while the lift coefficient deviations are more moderate, with a maximum of 3.54% for the same scale. Fixed Reynolds scaling, in which the Reynolds number is maintained constant by adjusting flow density, reduces aerodynamic deviations across all scales to below 0.056%, confirming the Reynolds number as the primary driver of scaling discrepancies. Subsequently, surface roughness and geometric shape optimisations using an Efficient Global Optimisation (EGO) framework are applied to assess their effectiveness in recovering baseline aerodynamic performance: roughness proves unable of addressing the pressure field deficit, while shape optimisation reveals a fundamental Pareto conflict between pressure and skin friction coefficients recovery.