Computational fluid dynamics (CFD) has an important role in current research. While large eddy simulations (LES) are now common practice in academia, Reynolds-averaged Navier–Stokes (RANS) simulations are still very common in the industry. Using RANS allows faster simulations, however, the choice of the turbulence model has a bigger impact on the results. An important influence of the turbulence modeling is the description of turbulent mixing. Experience has shown that often inaccurate simulations of combustion processes originate from an inadequate description of the mixing field. A simple turbulent flow and mixing configuration of major theoretical and practical importance is the jet in crossflow (JIC). Due to its good fuel-air mixing capability over a small distance, JIC is favored by gas turbine manufacturers. As the design of the mixing process is the key to creating stable low $NOx$ combustion systems, reliable predictive tools and detailed understanding of this basic system are still demanded. Therefore, the current study has re-investigated the JIC configuration under engine relevant conditions both experimentally and numerically using the most sophisticated tools available today. The combination of planar particle image velocimetry and laser induced fluorescence was used to measure the turbulent velocity and concentration fields as well as to determine the correlations of the Reynolds stress tensor $ui′uj′¯$ and the Reynolds flux vector $ui′c′¯$. Boundary conditions were determined using laser Doppler velocimetry. The comparisons between the measurements and simulation using RANS and LES showed that the mean velocity field was well described using the SST turbulence model. However, the Reynolds stresses and more so, the Reynolds fluxes deviate substantially from the measured data. The systematic variation of the turbulent Schmidt number reveals the limited influence of this parameter indicating that the basic modeling is amiss. The results of the LES simulation using the standard Smagorinsky model were found to provide much better agreement with the experiments also in the description of turbulent mixing.

We evaluate the accuracy of the actuator line model (ALM) approach by performing simulations for the NREL 5‐MW wind turbine in uniform inflow using three large eddy simulation codes. The power and thrust coefficients obtained using the three codes agree within 1% when the grid spacing m and are cross‐validated against blade element momentum (BEM) theory. We find that the results of ALM converge towards BEM theory without the need for tip correction when the numerical resolution is increased. For m, the difference between the power and thrust coefficient obtained using ALM and BEM is 4.5% and 2.1%, respectively, although we note that no absolute convergence between ALM and BEM can be obtained as both models use different assumptions, such as the use of a force projection method in the ALM. The difference in the local axial and tangential forces along the blades obtained from ALM simulations using m and m can be as large as 10%. The effect of the number of actuator points on the obtained turbine power and thrust coefficients is limited as the results converge when the spacing between the actuator points is about three times the grid spacing. This insight on the required number of blade points can be used to improve the efficiency of actuator line simulations.