Classical and AI Computational Fluid Dynamics: Research and Applications to Science and Engineering

Dear Colleagues,

The study of the flow of fluids is fundamental for understanding a large range of natural phenomena, engineering systems, and modern technologies. Examples range from most astrophysical systems, like the whole universe, galaxies, and stars, to understanding the weather, ocean currents, and tides; blood circulation; aircraft and automobiles; pipelines; water distribution systems; dispersion of contaminants in water, air, and soil, and so on. Understanding fluid flow is fundamental for medical applications, the environment, industry in general, and most energy systems. Numerical methods for fluid flow solve the governing equations of fluid dynamics, which are the foundation of computational fluid dynamics (CFD).  The main numerical methods for fluid flow are the finite difference method (FDM), the finite volume method (FVM), the finite element method (FEM), the spectral method, the lattice Boltzmann method (LBM), and the smoothed particle hydrodynamics method (SPH). Recently, artificial intelligence (AI) has been reshaping CFD by reducing computational costs, accelerating simulations, and learning the behavior of fluids from data. Topics of interest for this Special Issue include numerical simulations of fluid flow using the different methods we have mentioned above and applied to basic science and engineering. We encourage, in particular, submitting papers that use AI techniques and methods.

Prof. Dr. Jaime Klapp
Prof. Dr. Leonardo Di G. Sigalotti
Prof. Dr. J. E. V. Guzmán
Dr. Estela Mayoral
Guest Editors

Manuscript Submission Information

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