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CFD Events Calendar, Event Record #31737

Large-Eddy Simulation, Detached-Eddy Simulations and Machine Learning using a Python CFD code
A three-day ONLINE course on LES, DES, IDDES using an in-house Python CFD code. The third day we will work on Machine Learning methods for improving wall-functions and turbulence modeling
Date: July 1, 2024 - July 5, 2024
Location: On-line, Sweden
Web Page:
Contact Email:
Organizer: Flowsim AB
Application Areas: Turbomachinery, Automotive, Aerospace, Environmental, General CFD, Wind Turbines
Special Fields: Turbulence - LES Methods, Heat Transfer, Finite Volume Methods, Aeroacoustics & Noise, Aerodynamics, Incompressible Flows, Fluid Mechancis
Softwares: Python
Type of Event: Course, International

Most engineers and many researchers have limited knowledge of what a LES/DES CFD code is doing. Furthermore they don't know how to use Machine Learning for model development.

The object of this course is to close that knowledge gap. During the course, the participants will learn and work with an in-house LES/DES code called pyCALC-LES, written by the lecturer. It is a finite volume code written in Python. It includes two zero-equation SGS models (Smagorinsky and WALE) and two two-equation DES models (the PANS model and the k-omega DES model).

The Machine Learning model that will be used is Neural Network (NN). It is a Python module. NN will be used for improving wall functions and turbulence models.

All discretized equations in pyCALC-LES may be solved on the GPU if the computer has an Nvidia compatible graphics card. pyCALC-LES can also run fully on the GPU. On an eight million mesh, pyCALC-LES runs 40 times faster on the GPU than on the CPU.

The course includes lectures (12 hours) and workshops (12 hours) learning and working on Machine Learning and turbulence modeling in pyCALC-LES.

The number of participants is limited to 16.

The course fee is 16 300 SEK (approx 1450 Euro)

Event record first posted on March 9, 2024, last modified on March 12, 2024

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