About this Research Topic
In aerospace engineering, machine learning (ML) and artificial intelligence (AI) approaches are broadly used to address various issues and optimize the efficiency and performance of processes and systems. Ideas from aerospace and AI can cross-fertilize and help advance the multidisciplinary field of AI based on engineering.
This Research Topic is focused on the applications of ML and AI in airship design, hypersonic vehicle design, re-entry heating modeling, high-speed combustion, and shock wave-turbulent boundary layer interaction. The relevant topics are not limited to the above areas and thus research in the areas of aerodynamics, heat transfer, and computational fluid dynamics are also welcomed.
Our main aim in this Research Topic is to highlight the applications of ML and AI in the design and analysis of aerospace systems, with the scope of this collection including, but not being limited to, research in the following areas:
• The prediction of aerothermodynamic loads in hypersonic vehicles
• The prediction and/or correction of attitude angles in UAV’s
• Intelligent ice detection on wind turbine blades
• Shock boundary layer interactions
• The prediction of separation bubbles in high angle of attack airfoils
• The design of airships
• High speed combustion
• Aerofoil designs of UAV’s
• The design of space launch vehicles
• Trajectory path optimization of space launch vehicles
• Trajectory path optimization of UAV’s
• The design of wind turbines
• The design of high-speed vehicles (e.g. re-entry, drones etc.).
Original research articles as well as review/mini-review articles are welcome in this collection.
This Research Topic is focused on the applications of ML and AI in airship design, hypersonic vehicle design, re-entry heating modeling, high-speed combustion, and shock wave-turbulent boundary layer interaction. The relevant topics are not limited to the above areas and thus research in the areas of aerodynamics, heat transfer, and computational fluid dynamics are also welcomed.
Our main aim in this Research Topic is to highlight the applications of ML and AI in the design and analysis of aerospace systems, with the scope of this collection including, but not being limited to, research in the following areas:
• The prediction of aerothermodynamic loads in hypersonic vehicles
• The prediction and/or correction of attitude angles in UAV’s
• Intelligent ice detection on wind turbine blades
• Shock boundary layer interactions
• The prediction of separation bubbles in high angle of attack airfoils
• The design of airships
• High speed combustion
• Aerofoil designs of UAV’s
• The design of space launch vehicles
• Trajectory path optimization of space launch vehicles
• Trajectory path optimization of UAV’s
• The design of wind turbines
• The design of high-speed vehicles (e.g. re-entry, drones etc.).
Original research articles as well as review/mini-review articles are welcome in this collection.
Keywords: Machine Learning, Artificial Intelligence, Aerospace Systems, Physics Informed Neural Network, Aerodynamics, Heat Transfer, Computational Fluid Dynamics, Airship Design, Hypersonic Vehicle Design, Re-entry Heat Modeling, High-speed Combustion
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
