Using Physics Informed Neural Network (PINN) to Improve a k-omega Turbulence Model

pyCALC-RANS has now been extended with PINN.

• View paper
  
• Download the code here (18 MB, 2 July 2025)
• Flowchart
• pyCALC-RANS report. In Section 7.3 you find instructions on how to run the code.
  
• The PINN Python script is found in folder PINN and also found here
• Please read the README file

• Download the 3D DNS/LES/DES pyCALC-LES code here

• Prof. Lars Davidson www page
  
• MTF073 CFD course
  
• Heat Transfer course
  
• Mechanics of fluids
  
• Turbulence modeling
  
• Compressible flow
• OpenFOAM
  
• PhD course: LES and DES using an in-house Python code
  
• International MSc programme in Applied Mechanics
• PhD course in CFD