Assignment in Machine Learning for turbulence modeling

• The assignment is described in Appendix IMS135, Assignment on Machine Learning for Turbulence Modeling in the eBook
• All files zipped (all-files.zip)

• Channel, Re=550
  • Channel flow at Re550; file: Re550.dat
  • Channel flow at Re550, budget of k; file: Re550_bal_kbal.dat
  • Channel flow a Re=550, budget of u'u'; file: Re550.bal.uu
  • Channel flow a Re=550, budget of v'v'; file: Re550.bal.vv
  • Channel flow a Re=550, budget of w'w'; file: Re550.bal.ww
  • Channel flow a Re=550, budget of u'v'; file: Re550.bal.uv
  • Re550_bal_kbal.dat
  • read-channel-550.py

• Channel, Re=2000
  • read-channel-2000.py
  • Re2000_bal_k.dat
  • Re2000_jimenez.dat

• Channel, Re=5200
  • Channel flow a Re=5200, mean flow; file: LM_Channel_5200_vel_fluc_prof.dat
  • Channel flow a Re=5200, turb. quantities; file: LM_Channel_5200_mean_prof.dat
  • Channel flow a Re=5200, budget of k; file: LM_Channel_5200_RSTE_k_prof.dat
  • Channel flow a Re=5200, budget of uu; file: LM_Channel_5200_RSTE_uu_prof.dat
  • Channel flow a Re=5200, budget of vv; file: LM_Channel_5200_RSTE_vv_prof.dat
  • Channel flow a Re=5200, budget of ww; file: LM_Channel_5200_RSTE_ww_prof.dat
  • Channel flow a Re=5200, budget of uv; file: LM_Channel_5200_RSTE_uv_prof.dat
  • y_u_k_om_uv_5200-RANS-half-channel.txt
  • load channel data and NN model
  • LM_Channel_5200_vel_fluc_prof.dat
  • LM_Channel_5200_RSTE_k_prof.dat

• Channel, Re=10000
  • read-channel-10000.py
  • read k for channel Re=10000
  • read uu for channel Re=10000
  • read vv for channel Re=10000
  • read ww for channel Re=10000
  • Channel flow a Re=10 000, budget of u'u'; file: P10k.uu.txt
  • Channel flow a Re=10 000, budget of v'v'; file: P10k.vv.txt
  • Channel flow a Re=10 000, budget of w'w'; file: P10k.ww.txt
  • Channel flow a Re=10 000, budget of u'v'; file: P10k.uv.txt

• Flat-plate boundary layer
  • Boundary layer, mean flow; file: vel_11000_DNS.dat
  • Boundary flow, turb. quantities; file: bud_11000.prof
  • Boundary flow, load data

• Finite volume solvers
  • poisson-1D.py
  • RANS0.py

• PINN and NN
  • NN-train-non-linear-BL.py
  • vist-diffusion-pinn-5200-half-channel-save.ct
  • compute-vist-using-PINN-load.py
  • compute-vist-using-PINN-save.py
  • compute-constant-k-using-PINN.py
  • poisson-2D-PINN.py
  • compute-constant-vist-using-PINN-load.py
  • compute-constant-vist-using-PINN-save.py
  • NN-f2-5200-no-batch.py
  • slides 14 Int, National Conf. on Fluid Mechanics, Qingdao, China, 7-11 August 2026

• 2D DNS data
  • DNS data, wave
  • DNS data, hill
  • DNS data, expansion
  • DNS data, contraction

• 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