  We explore the applicability of MATLAB for 3D computational fluid dynamics
(CFD) of shear-driven indoor airflows. A new scale-resolving, large-eddy
simulation (LES) solver titled DNSLABIB is proposed for MATLAB utilizing
graphics processing units (GPUs). The solver is first validated against another
CFD software (OpenFOAM). Next, we demonstrate the solver performance in three
isothermal indoor ventilation configurations and the results are discussed in
the context of airborne transmission of COVID-19. Ventilation in these cases is
studied at both low (0.1 m/s) and high (1 m/s) airflow rates corresponding to
$Re=5000$ and $Re=50000$. An analysis of the indoor CO$_2$ concentration is
carried out as the room is emptied from stale, high CO$_2$ content air. We
estimate the air changes per hour (ACH) values for three different room
geometries and show that the numerical estimates from 3D CFD simulations may
differ by 80-150 % ($Re=50000$) and 75-140 % ($Re=5000$) from the theoretical
ACH value based on the perfect mixing assumption. Additionally, the analysis of
the CO$_2$ probability distributions (PDFs) indicates a relatively non-uniform
distribution of fresh air indoors. Finally, utilizing a time-dependent
Wells-Riley analysis, an example is provided on the growth of the cumulative
infection risk being reduced rapidly after the ventilation is started. The
average infection risk is shown to reduce by a factor of 2 for lower
ventilation rates (ACH=3.4-6.3) and 10 for the higher ventilation rates
(ACH=37-64). The results indicate a high potential for DNSLABIB in various
future developments on airflow prediction.
