Slawomir Wisniewski
Aeroelasticity Engineer · Structural Analysis
Warsaw, Poland
Aeroelasticity Engineer with 8 years of experience in static and dynamic aeroelastic analysis of aircraft structures. Uses NX Nastran SOL 144/145/146 for aeroelastic calculations and ZAERO for advanced flutter prediction. Works closely with aerodynamics and structural teams to ensure aeroelastic stability margins are met throughout the flight envelope.
Expertise
- static aeroelasticity
- flutter analysis (SOL 145)
- gust load analysis
- aero-structural coupling
- panel flutter
Technologies
Work History
2024-11
Trim analysis (SOL 144) for maneuver loads — n=+2.5 and n=-1.0 symmetric pullup and pushover, aileron roll, and engine-out yaw. Generated maneuver load envelopes for structural sizing.
Challenge: Engine-out yaw case produced asymmetric loads that were difficult to envelope with symmetric analysis. Had to run fully asymmetric aerodynamic model which required 3x more Nastran setup time than the symmetric cases.
Learned: Asymmetric load cases are disproportionately expensive in aeroelastic analysis because the aerodynamic model cannot exploit symmetry. Budget additional time when the design includes engine-out or asymmetric failure cases.
2024-06
Panel flutter analysis of fuselage skin panel — derived aerodynamic pressure using piston theory, performed eigenvalue analysis to find flutter dynamic pressure as function of Mach number.
Challenge: Piston theory is valid for M > 1.2 but the panel of interest also needed assessment at transonic speeds (M 0.8-1.2) where piston theory is inaccurate. Used ZAERO's ZONA7 method for transonic flutter prediction.
Learned: No single aerodynamic method covers the full flight envelope. Subsonic (DLM), transonic (ZONA7 in ZAERO), and supersonic (piston theory) methods are needed for different Mach ranges. Each has its own applicability limits.
2023-12
Discrete gust analysis (SOL 146) for composite wing under 1-cosine gust per FAR 25.341 — dynamic load factors at 20 stations along the span for structural sizing.
Challenge: The gust gradient distance (from 30 to 350 ft) sweep required 32 separate SOL 146 runs. Automating run submission and result extraction via Python was essential — manual operation would have taken a week.
Learned: FAR 25 gust analysis requires systematic sweep of all regulatory gust wavelengths — automation is not optional for this type of parametric study. Python + NX Nastran batch interface reduced the 32-run study to an overnight HPC job.
2023-08
Flutter analysis (SOL 145) — V-g diagram generation across Mach range 0.3-0.85, identification of flutter speed and frequency for each mode. Demonstrated sufficient flutter margin (>15% above VD).
Challenge: V-g diagram showed a 'hump' mode — a mode that becomes stable, then unstable again at higher speed. This mechanism is less intuitive than classic flutter and required careful explanation to the certification team.
Learned: Hump mode flutter is a coupling between structural modes that can appear stable on a V-g plot below the peak and then re-emerge at higher speed. The analysis must be run to well above VD to catch all potential instabilities.
2023-03
Static aeroelastic analysis (SOL 144) of composite wing — jig twist distribution required for washout under cruise aerodynamic load. Compared rigid vs flexible aerodynamic load distribution.
Challenge: Coupling between aerodynamic and structural models required matching aerodynamic panel grid to structural FEM grid via interpolation. Spline interpolation errors near the wingtip caused non-physical load distribution.
Learned: Spline quality at structural-aerodynamic model boundaries must be verified by visualizing the interpolated displacements. Bad splines produce non-physical warping that can mask real aeroelastic effects.