Canonical shock/turbulence interaction
A collection of averaged data for the DNS cases in Larsson et al (JFM 2013) and Larsson and Lele (PoF 2009) can be downloaded as a tar-file here. Once unpacked, the files are in ASCII format with a header that describes the contents of each file. This header should be read as follows:
- u means the average of the shock-normal velocity, u-F means the density-weighted (Favre) averaged value.
- u_x means the average of the shock-normal derivative of u; y and z are in the plane of the shock.
- r’r’ means the average of the density fluctuation squared (i.e., the variance).
- u”v”-F means the density-weighted average of the u-fluctuation times the v-fluctuation, where the fluctuation is defined with respect to u-F and v-F.
Note that the data in these files were averaged over a small set of 3D solution snapshots, so the profiles are relatively noisy. The Reynolds stresses (“Rij”) have units of velocity squared, i.e., without the density. Some quantities should be zero by symmetry or due to the periodic boundary conditions, but are included anyway.
Compressible turbulent boundary layers
Averaged profiles from some unpublished DNS cases can be downloaded as a tar-file here. There are 8 cases, covering Mach 2 to Mach 10, with cold, adiabatic, and heated walls. The Reynolds number is Re_{\delta2} \approx 2000. All cases use a calorically perfect gas with c_p/c_v=1.4; while not realistic at the highest Mach numbers, this helps isolate flow physics from other effects. Data is provided along the streamwise direction (wall quantities, boundary layer thickness, etc) and along the wall-normal direction from a location towards the end of the wall. The actual input files given to the code are provided as well, providing information on flow parameters like the gas constant R (set to produce a desired Mach number with unity free stream density, velocity and temperature) and the viscosity law (power-law, for simpler non-dimensionalization).
In addition, averaged profiles from some of the DNS cases in Volpiani et al (PRF 2020) can be downloaded from Pedro Volpiani’s website.