LES and DES using an in-house Python

The traditional method for CFD in industry and universities is Reynolds-Averaged Navier-Stokes (RANS). It is a fast method and mostly rather accurate. However, in flows involving large separation regions, wakes and transition it is inaccurate. The reason is that all turbulence is modeled with a turbulence model. For predicting aeroacoustic, RANS is even more unreliable. For these flow, Large-Eddy Simulation (LES) and Detached-Eddy Simulations (DES) is a suitable option although it is much more expensive. Still, in many industries (automotive, aerospace, gas turbines, nuclear reactors, wind power) DES is used as an alternative to RANS. In universities, extensive research has been carried out during the last decade(s) on LES and DES. Unfortunately, most engineers and many researchers have limited knowledge of what a LES/DES CFD code is doing. 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 Python code called pyCALCLES written by the lecturer. It is a finite volume code based on the CALC-LES code. The Python code is fully vectorized (it only includes two DO-loops (the time loop and the global iteration loop). It is reasonably fast.

pyCAKC-LES report

Lars Davidson lars.davidson@chalmers.se