Manuscript Topics

With the increasing availability of flow data from simulations and experiments, artificial intelligence and machine learning are revolutionizing the research paradigm in aerodynamics and related disciplines through enhancing modeling, optimization, control, and other applications. The integration of machine learning with theoretical, computational, and experimental investigations unlocks new possibilities for solving cutting-edge problems. Despite the successful applications, challenges still remain, especially regarding model generalization, interpretability, and the ability to learn from small datasets, which require further exploration.

This Special Issue focuses on novel techniques and their associated challenges in applying artificial intelligence to aerodynamics. We invite submissions on various topics, including but not limited to:
• Numerical methods (e.g., physics-informed machine learning)
• Theoretical modeling (e.g., turbulence closure, equation identification)
• Reduced-order models
• Aerodynamic optimization
• Flow control
• Data analysis and knowledge discovery
• Multiphysics applications

We welcome contributions that advance the understanding and application of artificial intelligence in aerodynamics and related fields.

Instruction for Authors
https://www.aimspress.com/mina/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/