Tommaso
Corradini

The project responds to evolving CS-25 airworthiness regulations, which place greater emphasis on the aerodynamic penalties of ice accretion on civil airliners. The aim was to quantify how realistic ice shapes change the lift and pitching-moment behaviour of a modern transport-aircraft high-lift system at full-scale Reynolds numbers.

It was carried out as a research project in collaboration with Airbus, the European Transonic Windtunnel (ETW), Boeing and NASA.

The wing cruises at M = 0.8, Re = 4 million and α = 2°. Applying simple sweep theory to the 25° quarter-chord sweep, the sections were designed in 2D at an effective Mach number of 0.725. The goal was a supercritical profile with a supersonic “rooftop” and an efficient, weak-shock pressure recovery, tracked through the Korn technology factor and the drag-divergence Mach number.

• First approach: designing at an effective angle of attack corrected for downwash (lifting-line theory) did not beat the baseline, with the Korn factor dropping to 0.85–0.88 and lift and efficiency down by about 2–3%.
• Final approach: designing at the fixed geometric angle, five candidates were produced. The selected one, TC04, raised the Korn factor from 0.88 to 0.91 and the drag-divergence Mach number from 0.711 to 0.715.
• Pressure distribution: TC04 replaces the original high-suction rooftop ending in a sharp shock at about 40% chord with a lower-suction rooftop extending to nearly 60% chord, followed by a much more gradual compression.
• Twist optimisation: with −0.6° of crank twist, the wing reached CL/CD = 24.6 at cruise, up to 5.5% more lift at low incidence and 6.6% less drag at 3.25°. A washout of −1° at the crank and −3° at the tip cut total drag by 5.6% at cruise and 14.3% at 3.5°, and extended the converged range to 3.5°, at the cost of about 5% lift.
• Buffet margin: the new design gains lift capability below M = 0.7 but reaches its buffet limit earlier above M = 0.78, because the crank carries more load and its local peak Mach rises to 1.25, a trade-off identified for further work.

Real flight paths were taken from ADS-B Exchange and converted into trajectory data. For every aircraft and every time step, the model computes the 3D distance to each point on the ground and applies a Noise–Power–Distance (NPD) law to estimate the sound exposure level.

• Directivity: jet noise is not isotropic, so a dipole-type directivity function makes the noise strongest along the flight axis and weakest to the sides.
• Thrust by flight phase: each trajectory point is classified from altitude and ground speed into taxi, take-off roll, climb, approach, landing roll or stopped, and assigned the matching ICAO LTO-cycle thrust setting.
• Noise contours: acoustic energy is accumulated over time and across all aircraft, converted back to SEL, and drawn as contours from 45 to 70 dBA, with the enclosed area of each level.
• Animation: the tool renders a video with adjustable speed and frame rate, showing aircraft moving over the map with their noise footprint.

The method is fast and can be adapted to any airport or flight, making it useful for exploring flight paths that reduce noise over densely populated areas. Its main limitations are that weather and terrain are not modelled, and aircraft are grouped by size category rather than by individual type.