Iran – Applications of deep learning in CFD and aerodynamics

Free #وبینار video, full introduction to the application of deep learning in aerodynamics and fluid mechanics.

Related courses:
Deep learning in introductory CFD
Deep learning in advanced CFD

09904971575

Aerospace Engineering Academy

📣 Online and offline training course

✅ “Applied deep learning in aerodynamics and fluids (introductory)” course

⏰ 28 hours
📅 Fridays from November 26
💰 from 9 to 13 – 1500 tomans
👨‍🏫 Teacher: Mr. Dr. Biki

Applied deep learning in aerodynamics and fluid mechanics

Objective of the course:

Deep learning has found many applications in the field of fluid mechanics due to the advances in computer hardware and having access to a huge amount of generated data. For example, the aerodynamic coefficients of any desired airfoil can be obtained with very high accuracy in less than one second. In addition, in the field of computational fluid dynamics, deep learning has helped to develop solvers that allow us to obtain the flow field around any desired object in much less time than conventional CFD solvers. Couple coding covers these two specialized areas of the most trending topics of artificial intelligence in the field of fluids. This course has an advanced level.

Course title

The basics of deep learning and the training of deep learning models (8 hours) The application of deep learning in Super resolution (10) hours – theory and programming The solution of PDE equations with the help of deep learning (6) hours – theory and programming Finding Dominant modes of the flow field with the help of deep learning (4) hours – Sensor data theory and programming

📣 #آنلاین and #آفلاین training course

✅ “Applied deep learning in CFD and aerodynamics (advanced)” course

⏰ 24 hours
📅 January 1402
💰 1500 thousand tomans
👨‍🏫 Teacher: Mr. Dr. Biki

Deep Learning in CFD Aerodynamics (Advanced)

Among the practical and innovative courses of the Deep Learning in CFD & Aerodynamics Academy, the aerospace course is for those who are interested in coupling the two worlds of CFD and artificial intelligence in an advanced form, considering the current trend and the focus of the world in their field of expertise. The course joins the club of advanced artificial intelligence in the field of CFD by completing the topics of the introductory course but at a professional level and by simulating up-to-date scholarly articles.

Objective of the course:

Improve Physical Understanding

Machine Learning

Accelerate Simulations, Improve Scaling

Direct Numerical Simulation

Turbulence Modeling (LES and RANSI

Reduced-Order Models

Course title

Chapter 1: Advanced topics in Super-resolution

:Reduced-Order Modeling, the second chapter of advanced topics in . E. Future prediction with recurrent networks

The challenge of disorganized networks

. The third chapter of advanced techniques in problem solving

Couple by optimizing meta-heuristic algorithms such as (PSO)