Large-eddy simulations (LES) of cavitating flow of a Diesel-fuel-like fluid in a generic throttle geometry are presented. Two-phase regions are modeled by a parameter-free thermodynamic equilibrium mixture model, and compressibility of the liquid and the liquid-vapor mixture is taken into account. The Adaptive Local Deconvolution Method (ALDM), adapted for cavitating flows, is employed for discretizing the convective terms of the Navier-Stokes equations for the homogeneous mixture. ALDM is a finite-volume-based implicit LES approach that merges physically motivated turbulence modeling and numerical discretization. Validation of the numerical method is performed for a cavitating turbulent mixing layer. Comparisons with experimental data of the throttle flow at two different operating conditions are presented. The LES with the employed cavitation modeling predicts relevant flow and cavitation features accurately within the uncertainty range of the experiment. The turbulence structure of the flow is further analyzed with an emphasis on the interaction between cavitation and coherent motion, and on the statistically averaged-flow evolution.@en

Preliminary results of large-eddy simulations of turbulent cavitating shear layers are presented. Validation of the computational setup is presented with focus on the extent of the spanwise domain size. We observe characteristic differences in the evolution of the extremal values of the components of the Reynolds-stress tensor at different cavitation numbers.@en

We present LES results of temporally evolving cavitating shear layers. Cavitation is modeled by a homogeneous equilibrium mixture model whereas the effect of subgrid-scale turbulence is accounted for by the Adaptive Local Deconvolution Method (ALDM). We quantitatively compare LES results with experimental data available in the literature. In terms of computational performance, we present a strong scaling study of our MPI-parallelized in-house FORTRAN code INCA on Cray XE6 “Hermit” at the High Performance Computeing Center Stuttgart (HLRS).@en