New Insights into Fluid Mechanics: Modeling and Computing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Fluid Science and Technology".
Deadline for manuscript submissions: 20 March 2025 | Viewed by 174
Special Issue Editors
Interests: bluff body (ships and vehicles) airwakes; active flow control; aircraft aerodynamics; wind turbine; turbomachinery; engine inlet
Interests: train aerodynamics and operation safety; wind engineering; CFD application with AI; flow control; comprehensive comfort evaluation of rail transit
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The field of fluid mechanics is experiencing a transformative phase, driven by rapid advancements in computational power, machine learning techniques, and innovative modeling approaches. This Special Issue, titled “New Insights into Fluid Mechanics: Modeling and Computing”, seeks to explore and disseminate cutting-edge research that pushes the boundaries of our understanding of the fluid mechanics domain.
A significant focus of this Special Issue is on the integration of machine learning in fluid mechanics. This emerging field leverages AI-driven models to predict fluid behavior. Of particular interest are data-driven turbulent models, which utilize vast datasets to enhance our ability to simulate and control turbulence in complex flows. These models enable more reliable and accurate predictions in areas where traditional methods fall short.
The Issue also seeks contributions to innovations in turbulence modeling, particularly in the development and application of Large Eddy Simulations (LES) and Direct Numerical Simulations (DNS), which are crucial for improving our understanding of turbulent flows in a variety of contexts, from aerospace engineering to environmental sciences.
Multiphase flow and fluid–structure interaction (FSI) form other critical areas of focus. Multiphase flow dynamics involves the complex interaction of multiple phases, challenging traditional models. Advances in computational techniques and machine learning offer new insights for accurate simulations. Fluid–structure interaction (FSI) deals with the coupling between fluid flows and structural responses, where improved algorithms and high-performance computing can lead to more efficient modeling.
Finally, the Special Issue will cover advanced flow control simulations, such as those with complex actuators, those leading to the advanced understanding of flow control mechanisms, etc. Furthermore, machine learning-driven flow control strategies are of great interest, which explore how computational techniques and AI can be harnessed to manipulate and optimize fluid flows for performance enhancement.
Dr. Kewei Xu
Dr. Zhengwei Chen
Guest Editors
Dr. Xiao Xue
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- machine learning
- data-driven method
- turbulent modeling
- flow control
- multiphase flow
- flow–structure interaction
- lattice Boltzmann methods
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