Advances and Applications of Machine Learning in Fluid Flow Problems

Prof. Mohamed Fathy El-Amin Mousa is a distinguished full professor of applied mathematics and computational sciences at Effat University, Saudi Arabia, and Aswan University, Egypt. With a career spanning more than 25 years, Dr. El-Amin has established a global reputation for pioneering contributions in computational modeling, fluid dynamics, reservoir simulation, porous media transport, heat and mass transfer, hydrogen energy, and renewable energy technologies.He earned his Ph.D. in Applied Mathematics. His postdoctoral journey included prestigious fellowships from the Alexander von Humboldt Foundation in Germany and the Japan Society for the Promotion of Science (JSPS) in Japan, as well as research appointments at renowned institutions such as Stuttgart University, Kyushu University, King Abdullah University of Science and Technology (KAUST), and the University of Texas at Austin.Dr. El-Amin has published over 200 peer-reviewed articles, book chapters, and conference papers, alongside several edited volumes and special journal issues. His recent authored books, including Numerical Modeling of Nanoparticle Transport in Porous Media (Elsevier, 2023) and Fractional Modeling of Fluid Flow and Transport Phenomena (Elsevier, 2025), reflect his leadership in bridging mathematical theory with practical energy and environmental challenges.Currently, Dr. El-Amin leads research projects on atmospheric water generation using desiccant materials and underground hydrogen storage, aiming to support sustainable energy and water security initiatives. His research innovations have led to patents and new prototype developments, particularly involving carbon nanotubes and graphene-based technologies.An active member of several international scientific societies, including INTERPORE and the Society of Petroleum Engineers (SPE), Dr. El-Amin has been consistently recognized among the World’s Top 2% Scientists by Stanford University rankings. His contributions have earned him multiple awards for excellence in research, teaching, and civic engagement.Beyond research, Dr. El-Amin is deeply committed to mentoring graduate students, supervising numerous MSc and Ph.D. theses, and actively participating in university leadership roles, including chairing promotion and research committees. His philosophy emphasizes interdisciplinary collaboration and the real-world application of scientific knowledge to meet the global challenges of energy, water, and sustainability.

• Table of ContentsBiographyList of figuresList of tables Part I Introduction Chapter 1Overview of Machine Learning Chapter 2 Challenges, Limitations, and Recommendations Part II ML for Turbulent Flows Chapter 3 PIV, CFD and ML for Turbulent Jet Chapter 4 Turbulent Jets Using Time Series Chapter 5 Machine Learning for Permeability Chapter 6 Hybrid Forecasting for Petroleum Reservoir Chapter 7 PINN for Second-Order Porous Medium Part IV ML for Hydrogen Energy Chapter 8 Hydrogen Migration in Porous Media Chapter 9 Hydrogen Leakage Part V ML for Wind Energy Chapter 10 Wind Farm Optimization and ML