Computational Fluid Dynamics for Next-Generation Unmanned Aerial Vehicles

Dear Colleagues,

Urban Air Mobility (UAM) is an emerging transportation sector aiming to introduce new aerial platforms, such as Unmanned Aerial Vehicles (UAVs), for the movement of people and goods within urban environments. These services are expected to enhance the efficiency of urban transport by reducing commuting times, lowering transportation costs, and minimising the carbon footprint of such operations. However, these operations involve considerable risk, as UAV flight is highly sensitive to wind conditions. In particular, factors such as turbulence and wind gusts can compromise aircraft stability, posing a risk to public safety. These phenomena are especially prevalent in urban areas, where wind interactions with buildings and other structures lead to wake formation and vortex shedding, potentially jeopardising safe operations.

This Special Issue welcomes studies that explore innovative Computational Fluid Dynamics (CFD) approaches for wind forecasting in Urban Air Mobility applications. We encourage submissions that propose novel methods for mitigating the impact of turbulence and wind gusts on UAV flight. While the issue is primarily focused on CFD-based forecasting techniques—such as traditional Finite Volume Solvers, Physics-Informed Neural Networks (PINNs), and real-time strategies like Reduced Order Models—other relevant studies, including turbulence assessments and validation efforts, are also welcomed.

Topics of interest include, but are not limited to the following:

• AI-based wind forecasting
• Urban CFD-based wind prediction systems
• 3D modelling tailored for CFD simulations
• Wind turbulence assessments and CFD model validation
• Reduced Order Modelling and real-time wind forecasting
• Aerodynamic charaterization of Unmanned Aerial Vehicles

Dr. Enrique Aldao Pensado
Dr. Fernando Veiga López
Dr. Elena Beatriz Martín Ortega
Guest Editors

Manuscript Submission Information

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• computational fluid dynamics
• urban air mobility
• reduced order models
• AI-enhanced flow prediction
• wind turbulence
• urban wind forecasting
• microweather
• wind gusts
• wind-aware path planning