Numerical simulation and comparison of two ventilation methods for a restaurant – displacement vs mixed flow ventilation

Abstract

This paper presents a comparison between a displacement ventilation method and a mixed flow ventilation method using computational fluid dynamics (CFD) approach. The paper analyses different aspects of the two systems, like the draft effect in certain areas, the air temperatureand velocity distribution in the occupied zone. The results highlighted that the displacement ventilation system presents an advantage for the current scenario, due to the increased buoyancy driven flows caused by the interior heat sources. For the displacement ventilation case the draft effect was less prone to appear in the occupied zone but the high heat emissions from the interior sources have increased the temperature gradient in the occupied zone. Both systems have been studied in similar conditions, concentrating only on the flow patterns for each case.

Digital-twin-controlled ventilation for real-time resilience against transmission of airborne infectious disease in an indoor food court

“…The seat turnover rates in food courts during meal times tend to be high with many different individuals using the spaces, yet the typical seating durations are sufficiently long for the diners’ exposures to infectious aerosols to reach unsafe levels should there be an infectious diner within their vicinity. The food court selected as the case study, which was adapted from Chitaru et al, 35 was a mechanically ventilated cafeteria in Constanta, Romania. The food court had dimensions of 26.5 m × 11.25 m × 3.2 m (length × width × height) with an opening of size 4 m × 2 m that served as both the entrance and exit of the enclosed area (Figure 6).…”

Quantifying spatiotemporal variability in occupant exposure to an indoor airborne contaminant with an uncertain source location

“…Their ability to model the influence of complex airflow patterns on airborne contaminant transport has been studied in both experimental (Jayaraman et al 2006;Yin et al 2009; Barbosa and de Carvalho Lobo Brum 2021;Fu et al 2022) and real-world settings (Ho 2021), for a variety of enclosed spaces. Studies have applied CFD methods to investigate spatial distributions of contaminants in medical settings (Méndez et al 2008;Qian et al 2009;King et al 2013;Hang et al 2015;Bhattacharyya et al 2020), on public transportation (Zhu et al 2012;Li et al 2016;Yan et al 2017;Yang et al 2020), in classrooms (Abuhegazy et al 2020;Ascione et al 2021;Mirzaie et al 2021), at restaurants (Chitaru et al 2018;Ho 2021), and in different office settings (Lee et al 2009;Kong et al 2015;Barbosa and de Carvalho Lobo Brum 2021;Castellini et al 2022), often with the aim of understanding the influence of particular boundary conditions on in-room contaminant distributions. However, the added model fidelity of these methods increases the computational burden and information needed, making them impractical for some applications (Morozova et al 2020).…”