Manuscript Topics

This Special Issue focuses on the application of Artificial Intelligence (AI) and advanced mathematical methods in Fluid Mechanics. The rapid advancements in these computational fields are transforming various engineering disciplines, and Fluid Mechanics is no exception. The goal of this Special Issue is to highlight the latest research and innovations where modern computational techniques are applied to solve complex problems in Fluid Mechanics.
In recent years, techniques such as Machine Learning, Neural Networks, and optimization algorithms, alongside developments in numerical analysis and computational mathematics, have been increasingly utilized to enhance Computational Fluid Dynamics (CFD), optimize flow control, and improve the accuracy of simulations. Applications range from aerodynamics design, turbulence modeling, and weather forecasting to the development of efficient energy systems, including wind turbines and hydraulic structures. The use of advanced computational approaches in fluid flow prediction and control, as well as in the intelligent design of fluidic devices, is showing significant promise.
Moreover, these data-driven and mathematically-founded approaches in fluid mechanics are playing a critical role in various industrial and environmental sectors, offering innovative solutions for fluid-structure interactions, multiphase flow analysis, and the management of complex fluid systems. This Special Issue seeks contributions that explore these advancements, offering insights into the future of computational and mathematical applications in fluid mechanics.
We invite original research articles, reviews, and case studies that demonstrate the integration of modern computational and mathematical techniques in fluid mechanics, aiming to foster a comprehensive understanding of how these methods are reshaping this fundamental field of engineering.

Keywords

• Artificial intelligence
• Machine learning
• Deep learning
• Artificial neural networks
• Reinforcement learning
• Computational mathematics
• Numerical analysis
• Scientific computing
• Numerical models
• Mathematical models
• Mathematical analysis
• Computational fluid dynamics (CFD)
• Aerodynamics
• Design optimization

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