Dynamics and Control of Aircraft Wake Vortices

Aircraft wake vortices are pairs of counter-rotating, helical structures shed from the wingtips of lifting surfaces. Their self-induced descent and mutual interaction govern the spatial and temporal evolution of the wake, leading to instabilities, decay and eventual dissipation. External factors such as ambient turbulence, crosswinds and ground effect modulate vortex strength, trajectory and lifetime, creating complexity in safety separation criteria at airports. Wake vortices pose collision hazards to following aircraft, drive noise generation and limit airport throughput. Advances in experimental measurement (for example, LiDAR sensing), high-fidelity simulation (LES, adaptive meshing, turbulence modelling) and data-driven techniques (machine learning, dynamic mode decomposition) have enriched understanding of vortex generation, instability mechanisms (notably long-wave Crow modes and higher-frequency secondary modes) and controlled decay. Passive devices such as winglets, active flow control systems and dynamic separation protocols seek to mitigate wake hazards, enhance operational efficiency and reduce environmental impact. Emerging frameworks integrate real-time sensing with predictive algorithms to adapt separation minima to prevailing meteorological conditions, underscoring the global significance of coordinated dynamics and control strategies.

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Dynamics and Control of Aircraft Wake Vortices publication trend

The graph below shows the total number of articles in dynamics and control of aircraft wake vortices across all publications each year (not limited to Nature Index journals).

Technical terms

Wake vortex: A pair of counter-rotating, trailing vortices formed at wingtip edges during lift generation.

Crow instability: A long-wavelength sinuous instability that links counter-rotating wake vortices, leading to eventual breakdown.

Convolutional neural network (CNN): A machine learning architecture that applies spatially localised filters to predict complex patterns, such as vortex strength fields.

Light Detection and Ranging (LiDAR): A remote‐sensing technique that measures wind velocity and vortex structures by analysing scattered laser pulses.

Large eddy simulation (LES): A computational method that resolves large turbulent eddies while modelling smaller scales to capture unsteady vortex dynamics.

References

1. Prediction of Aircraft Wake Vortices under Various Crosswind Velocities Based on Convolutional Neural Networks. Sustainability (2023).
2. Characterizing aircraft wake vortex position and strength using LiDAR measurements processed with artificial neural networks.. Optics Express (2022).
3. Numerical Study of Aircraft Wake Vortex Evolution under the Influence of Vertical Winds. Applied Sciences (2023).
4. Higher order dynamic mode decomposition of an experimental trailing vortex. Physics of Fluids (2022).
5. Numerical simulation of aircraft wake vortex evolution and wake encounters based on adaptive mesh method. Engineering Applications of Computational Fluid Mechanics (2020).