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Kamila Kozioł

Aeroelasticity Engineer · Flight Dynamics & Aeroelasticity

Warsaw, Poland

Aeroelasticity Engineer specializing in flutter analysis and aeroelastic loads certification for commercial aircraft. Leads flutter analysis campaigns using NASTRAN SOL 145 with DLM unsteady aerodynamics, and develops W2GJ aerodynamic corrections for flutter and dynamic response. Works closely with structural analysis and CFD teams to integrate structural stiffness and aerodynamic correction factors into the aeroelastic model.

Expertise

  • flutter analysis (NASTRAN SOL 145)
  • aeroelastic stability certification (CS-25.629)
  • wing-pylon-engine aeroelastic coupling
  • aeroelastic effects on static loads
  • gust response aeroelastic correction

Technologies

NASTRAN SOL 145/146 ZAERO Python MATLAB MSC Patran Linux HPC Git

Work History

2025-02

Aeroelastic surrogate model for loads optimization — built a response surface model mapping structural design variables (spar cap thickness, rib pitch) to flutter speed and gust loads. Used in structural optimization loop.

Challenge: Flutter speed is a non-smooth function of structural parameters — it can jump discontinuously when flutter mode shapes switch between configurations. Surrogate models trained across mode shape discontinuities produced large prediction errors. Required separate surrogates for each flutter mode family.

Learned: Aeroelastic surrogates must be trained within mode shape families, not across mode switching boundaries. If structural optimization spans multiple flutter mode families, use clustering to identify the boundaries and train separate surrogates for each family.

Python scikit-learn NASTRAN SOL 145

2024-06

CS-25.629 flutter compliance demonstration — prepared the flutter substantiation report showing 15% flutter margin above VDF/MDF for all structural configurations. Coordinated with the DER for the analysis methodology approval.

Challenge: One structural configuration (minimum fuel, forward CG, flaps extended) showed flutter margin of 11% — 4% below the requirement. Required a structural stiffening modification at the wing root, which needed aeroelastic re-analysis, and a structural weight growth of 18 kg.

Learned: Flutter compliance must be checked for all structural configurations defined in the flutter substantiation plan — minimum fuel state with extended flaps is a standard low-stiffness case that is easy to overlook. Build an automated compliance summary that checks all configurations against the 15% margin before the substantiation report is finalized.

NASTRAN SOL 145 Python Confluence

2023-11

W2GJ aerodynamic correction factors — computed DLM-to-CFD pressure correction factors for the wing using NASTRAN ZONA7 lifting surface and 3D Euler CFD. Applied W2GJ corrections to improve flutter prediction fidelity.

Challenge: W2GJ correction factors are computed at specific Mach numbers and reduced frequencies — interpolating between these to apply in the SOL 145 flutter analysis required careful handling of the correction factor frequency dependence. Wrong interpolation led to non-physical damping oscillations.

Learned: W2GJ correction factor interpolation must preserve the reduced frequency dependence of the aerodynamic correction. Linear interpolation in frequency is not appropriate for W2GJ factors — use cubic spline interpolation with monotonicity constraints to avoid oscillatory interpolation artifacts.

NASTRAN SOL 145 ZAERO Python Linux HPC

2023-04

Flutter analysis for wing-engine-pylon configuration — NASTRAN SOL 145 V-g analysis across the flight envelope. Identified a potential wing-body-pylon coupling flutter mode at high fuel state and low damping.

Challenge: Wing-engine coupling flutter is dominated by engine pitch/yaw on pylon stiffness interaction — a mode that requires accurate pylon stiffness from the structural model. Initial pylon stiffness from early FEM was 15% stiffer than the final design, changing the flutter speed by 8%.

Learned: Aeroelastic flutter analysis is highly sensitive to pylon stiffness. Flutter analysis with preliminary pylon stiffness data produces results that can differ significantly from the final design — always update the flutter model as structural design matures and track the flutter speed sensitivity to pylon stiffness.

NASTRAN SOL 145 Python MSC Patran Linux HPC