Ventilation characteristics of the Columbus module are numerically predicted on the basis of the Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) approaches. The steady-state RANS computations were performed using the high-Reynolds-number k-ε turbulence model, and the Smagorinsky-Lilly subgrid-scale model was used for LES. The computed results were compared with experimental data available for spatial distributions of the time-averaged absolute velocity magnitude. On the basis of LES data, distinctions in the fields of this quantity and the whole mean velocity were analysed. A procedure for evaluation of the time-averaged absolute velocity spatial distributions using RANS data on the mean velocity and the turbulent kinetic energy is suggested and examined

This paper presents and discusses the results of the “2022 International Computational Fluid Dynamics Challenge on violent expiratory events” aimed at assessing the ability of different computational codes and turbulence models to reproduce the flow generated by a rapid prototypical exhalation and the dispersion of the aerosol cloud it produces. Given a common flow configuration, a total of 7 research teams from different countries have performed a total of 11 numerical simulations of the flow dispersion by solving the Unsteady Reynolds Averaged Navier–Stokes (URANS) or using the Large-Eddy Simulations (LES) or hybrid (URANS-LES) techniques. The results of each team have been compared with each other and assessed against a Direct Numerical Simulation (DNS) of the exact same flow. The DNS results are used as reference solution to determine the deviation of each modeling approach. The dispersion of both evaporative and non-evaporative particle clouds has been considered in 12 simulations using URANS and LES. Most of the models predict reasonably well the shape and the horizontal and vertical ranges of the buoyant thermal cloud generated by the warm exhalation into an initially quiescent colder ambient. However, the vertical turbulent mixing is generally underpredicted, especially by the URANS-based simulations, independently of the specific turbulence model used (and only to a lesser extent by LES). In comparison to DNS, both approaches are found to overpredict the horizontal range covered by the small particle cloud that tends to remain afloat within the thermal cloud well after the flow injection has ceased.