Artificial Intelligence for Computational Fluid Dynamics

Erscheinungsjahr 2025
ISBN: 978-0-443-29118-0
Verlag: Elsevier Science

Buch, Englisch, 540 Seiten, Format (B × H): 152 mm x 229 mm

Artificial Intelligence for Computational Fluid Dynamics serves as a comprehensive reference guide, providing up-to-date information on the utilization of high-performance computing and artificial intelligence (AI) in computational fluid dynamics (CFD). It caters to the needs of students and researchers, offering a single, comprehensive document encompassing machine learning, deep learning, neural networking, and their significance within the realm of CFD. The content not only covers the current state of the field but also provides insights into future research directions, emphasizing the importance of ongoing research and development. Additionally, the book introduces various scientific tools and software commonly employed in AI-based CFD applications. The newly amended CFD vision for 2030 receives specific attention, ensuring alignment with the latest advancements and industry trends. The editors and authors of this book are esteemed researchers with extensive experience in both teaching and research, establishing their expertise in the field.

Autoren/Hrsg.

Ahmad, Kamarul Arifin

Jawaid, Mohammad

Singh, Balbir

Fachgebiete

• Naturwissenschaften Physik Mechanik Kontinuumsmechanik, Strömungslehre
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Strömungslehre

Inhaltsverzeichnis

1. Artificial Intelligence and Computational Fluid Dynamics: Background
2. Introduction to artificial intelligence and subsets
3. Artificial intelligence based computational fluid dynamics approaches
4. Enhanced reduced order modeling and accelerated direct numerical simulation
5. Machine learning/ Deep Learning architectures and Computational Fluid Dynamics
6. Turbulence Closure Modeling using Deep Learning
7. DNNs - CNNs/RNNs/PINNs/cPINNs/xPINNs
8. ANN as popular AI tool for CFD
9. Support Vector Machine (SVM) an important Supervised Learning Category
10. Current AI algorithms in CFD and implementation
11. AI for accelerated CFD and fluid flow optimization
12. Dynamic Model Decomposition of complex Fluid Flow Analysis using Machine Learning
13. Machine learning based optimal mesh generation and optimization
14. Machine learning based New sparse algorithms
15. Commercial and open source models/codes used in industry for AI and CFD
16. Modern tools, languages and systems available for implementing AI algorithms.
17. Aerodynamic Modeling in CFD using AI
18. Application of AI for Turbulence Modeling
19. Application of AI in CFD for Boundary layer and Multiphase Flows
20. AI in Heat and Mass Transfer using CFD
21. AI for CFD in materials industry and other applications
22. Operating challenges for AI in CFD and the available solutions
23. AI, CFD and CFD Vision 2030
???23. Conclusion Remarks

Über Autor(innen)

Ahmad, Kamarul Arifin
Dr. Kamarul specializes in bio-inspired flight, advanced aerospace materials, computational and experimental aerodynamics, computational biomedics, machine learning in CFD, and launch vehicle dynamics. With a strong dedication to research over the past 15 years, he has authored or co-authored over 100 journals and conference proceedings. These publications cover diverse fields, including fluid dynamics, heat transfer, and bio-medical engineering. His works encompass articles in national and international journals (100 papers - Scopus), conference papers (53 papers), authored books (2), and edited books (2).

Dr. Kamarul's contributions have received significant recognition, evident through his impressive indexed citations (700) and h-index (16). He actively contributes to the scientific community as an editorial board member for renowned journals like ASEAN Engineering Journal and Aircraft and Spacecraft Journal. Additionally, he serves as a reviewer for various reputable journals. His mentorship has also led to successful supervision of doctoral and master's students.

In terms of research grants, Dr. Kamarul has completed more than 8 projects, totaling RM 2 million in funding. These grants have facilitated his research endeavors and advancements in the field.

Jawaid, Mohammad
Dr. Mohammad Jawaid is currently affiliated with the Department of Chemical and Petroleum Engineering at United Arab Emirates University. Previously he was a senior fellow (professor) in the Laboratory of Biocomposites Technology at the Institute of Tropical Forestry and Forest Products (INTROP), Universiti Putra Malaysia. He is an eminent scientist with more than twenty years of teaching, and research experience in composite materials. His research interests include hybrid reinforced/filled polymer composites, and advanced materials such as graphene/

nanoclay/fire retardant, lignocellulosic reinforced/filled polymer composites, and the modification and treatment of lignocellulosic fibres and solid wood, and nanocomposites and nanocellulose fibres.

Singh, Balbir
He is currently an aerospace researcher in the Department of Aerospace Engineering, Faculty of Engineering. Universiti Putra Malaysia. He has good number of publications and research grants in his favour. His research focus on insect inspired miniaturized robots for planetary studies, advanced aerospace materials (bio, natural or Nano) at all the scales, CFD, high performance computing and modelling, unsteady aerodynamics, space debris removal and space systems engineering.