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

pyCALC-RANS has now been extended with PINN and NN.

• Lars Davidson, "Using Physics Informed Neural Network (PINN) and Neural Network (NN) to Improve a k-omega Turbulence Model", Journal of Turbulence, https://doi.org/10.1080/14685248.2026.2665148, 1-22, 2026
  view paper
  
• Download the PINN and NN Pythons scripts and the CFD code here (48 MB, 3 May 2026) Read README file.
• The hill flow case is found in pyCALC-LES
• Flowchart
• pyCALC-RANS report. In Section 11.3 you find instructions on how to run the code.
  
• Please read the README file

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

• 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