Mathematical and Computational Fluid Mechanics: Algorithms, Modeling and PINNs
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 50
Special Issue Editor
Special Issue Information
Dear Colleagues,
Computational Fluid Mechanics is a vital area within engineering and applied sciences, dedicated to understanding and solving complex fluid-flow problems using mathematical models and advanced computational algorithms. In this context, Fluid Mechanics refers to the behaviour, motion, and interaction of fluids under various physical conditions—phenomena that remain central to many scientific and industrial applications.
We are pleased to announce this Special Issue of Mathematics, titled “Mathematical and Computational Fluid Mechanics: Algorithms, Modeling and PINNs.” This Special Issue will highlight recent advances in numerical modelling, algorithmic development, and data-driven methods, with particular emphasis on Physics-Informed Neural Networks (PINNs) and their integration with established computational techniques.
We invite contributions that address innovative theoretical developments, cutting-edge numerical algorithms, and impactful applications in fluid mechanics. Potential topics include, but are not limited to:
• Isogeometric Analysis (IGA);
• Deep Learning and Physics-Informed Neural Networks (PINNs);
• Finite Volume Method (FVM);
• Finite Element Method (FEM);
• Discontinuous Galerkin Method (DGM);
• Variational Multiscale Method (VMS);
• Fluid–Structure Interaction (FSI);
• Cardiovascular Simulations.
This Special Issue aims to bring together state-of-the-art research and innovative applications in mathematical and computational fluid mechanics, fostering collaboration and knowledge exchange across the community. We welcome high-quality submissions that advance modelling and simulation techniques and demonstrate their significance in addressing real-world engineering and scientific challenges.
Dr. Yousef Ghaffari Motlagh
Guest Editor
Manuscript Submission Information
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Keywords
- isogeometric analysis (IGA)
- deep learning and physics-informed neural networks (PINNs)
- finite volume method (FVM)
- finite element method (FEM)
- discontinuous Galerkin method (DGM)
- variational multiscale method (VMS)
- fluid–structure interaction (FSI)
- cardiovascular simulations
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