The aim of the present study is to analyze the performances of unsteady Reynolds-averaged Navier–Stokes (URANS) and large eddy simulation (LES) approaches in predicting the airflow patterns inside car cabins and to give insight in the design of computational fluid dynamics simulations of a real car cabin. For this purpose, one eddy viscosity-based turbulence model (shear stress transport k–ω) and two subgrid scale models (wall-adapting local eddy-viscosity and dynamic kinetic energy) were tested, and numerical results were compared with particle image velocimetry measurements carried out on a commercial car. The URANS model exhibited great accuracy in predicting the mean flow behavior and was appreciably outperformed by the LES models only far from the inlet sections. For this reason, it was deemed suitable for conducting further analyses, aimed at characterizing the airflow patterns in winter and summer conditions and performing a thermal comfort analysis. The thermal regime was found to have a very little effect on the air flow patterns, once the quasi-steady state regime is achieved; in fact, both in winter and in summer, the temperature field is fairly uniform within the car cabin, making the contribution of buoyancy negligible and velocity fields to be very similar in the two seasons. Findings also reveal that thermal comfort sensation can be different for passengers sharing the same car but sitting on different seats; this aspect should be considered when designing and operating the ventilation system, since the minimum comfort requirements should be met for all the occupants.

1. The car cabin is a controlled indoor environment where people spend significant time, whether for daily commutes or long-distance travel (European Communities 2004; Buonanno et al. 2011). Mainta...

Objective: To assess whether wind-driven natural ventilation in the Infectious Diseases Treatment Module (IDTM) can achieve ventilation performance consistent with airborne precaution requirements [160 liters per second (L/s)] and to estimate associated pathogen-specific infection risks. Methods: An experimental campaign of air velocity measurements and CO ₂ decays were conducted to validate the developed computational fluid dynamics (CFD) model. The validated CFD model simulated wind-driven natural ventilation (1–4 m/s) for an L-shaped IDTM configuration under four structural scenarios defined by the presence or absence of patient porches and mosquito nets. Airborne infection risk was estimated using a Wells–Riley quanta-based model for seven representative airborne pathogens under short-duration healthcare worker exposure and prolonged patient co-exposure. Results: Ventilation performance varied widely based on wind speed and structural configuration. Airflow ranged from 7 L/s in the most restricted configuration (porch and mosquito nets present at 1 m/s) to over 3,100 L/s when mosquito nets were removed at 4 m/s. When mapped to infection-risk estimates, ventilation rates at 160 L/s substantially reduced short-duration healthcare worker infection risk for all pathogens (≤1%), whereas prolonged co-exposure remained associated with high risk for high-emission pathogens despite high ventilation. Conclusion: Under favorable wind conditions and optimized configurations, the IDTM can achieve ventilation rates consistent with the 160 L/s recommendation for airborne precautions. While this provides substantial protection for healthcare workers, individual-room isolation remains essential for patient management. Operationally, removing window-mounted nets is the most effective way to ensure safety targets are met; hybrid ventilation measures should be considered during low-wind conditions.