Special Issue: Artificial Intelligence Methods for Applied Fluid Mechanics

Guest Editors

Dr. Unai Fernandez Gamiz
University of the Basque Country, Department of Nuclear Engineering and Fluid Mechanics, Engineering College at Vitoria-Gasteiz, Spain
Email: unai.fernandez@ehu.eus


Dr. Koldo Portal Porras
University of the Basque Country, Department of Electrical Engineering, Engineering College at Vitoria-Gasteiz, Spain
Email: koldo.portal@ehu.eus


Dr. Samad Noeiaghdam
Department of Mathematics, Henan Academy of Sciences, China
Email: snoei@hnas.ac.cn

Manuscript Topics

This Special Issue focuses on the application of Artificial Intelligence (AI) in Fluid Mechanics. The rapid advancements in AI 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 AI methods are applied to solve complex problems in Fluid Mechanics.  
In recent years, AI techniques such as Machine Learning, Neural Networks, and optimization algorithms 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 AI in fluid flow prediction and control, as well as in the intelligent design of fluidic devices, is showing significant promise.  
Moreover, AI-driven 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 AI applications in fluid mechanics.  
We invite original research articles, reviews, and case studies that demonstrate the integration of AI in fluid mechanics, aiming to foster a comprehensive understanding of how AI is reshaping this fundamental field of engineering.


Keywords

• Artificial Intelligence  
• Machine Learning  
• Deep Learning  
• Artificial Neural Networks  
• Reinforcement Learning  
• Numerical models  
• Mathematical models  
• Mathematical analysis  
• Computational Fluid Dynamics (CFD)  
• Aerodynamics  
• Design optimization


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Please submit your manuscript to online submission system
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Paper Submission

All manuscripts will be peer-reviewed before their acceptance for publication. The deadline for manuscript submission is 31 December 2025

Published Papers(2)