Artificial Intelligence for Computational Fluid Dynamics

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