Human exhalation characterization with the aid of schlieren imaging technique. (1st February 2017)

• Record Type: Journal Article
• Authors: Xu, Chunwen; Nielsen, Peter V.; Liu, Li; Jensen, Rasmus L.; Gong, Guangcai
• Is Part Of: Building and environment. Volume 112(2017)
• Page Start: 190
• Page End: 199
• Publication Date: 2017-02-01
• Subjects: Disease transmission -- Schlieren photography -- Exhaled airflow -- Propagation velocity -- Airflow interaction; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2016.11.032
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: The purpose of this paper is to determine the dispersion and distribution characteristics of exhaled airflow for accurate prediction of disease transmission. The development of airflow dynamics of human exhalation was characterized using nonhazardous schlieren photography technique, providing a visualization and quantification of turbulent exhaled airflow from 18 healthy human subjects whilst standing and lying. The flow shape of each breathing pattern was characterized by two angles and averaged values of 18 subjects. Two exhaled air velocities, u m and u p, were measured and compared. The mean peak centerline velocity, u m was found to decay correspondingly with increasing horizontal distance x in a form of power function. The mean propagation velocity, u p was found to correlate with physiological parameters of human subjects. This was always lower than u m at the mouth/nose opening, due to a vortex like airflow in front of a single exhalation cycle. When examining the talking and breathing process between two persons, the potential infectious risk was found to depend on their breathing patterns and spatial distribution of their exhaled air. Our study when combined with information on generation and distributions of pathogens could provide a prediction method and control strategy to minimize infection risk between persons in indoor environments. Highlights: Noninvasive schlieren technique was applied to characterize human exhalation. New methods were proposed to predict exhaled velocity um and up, respectively. Potential infection risk depended on breathing patterns and spatial distribution of exhaled air. New data was added to airflow dynamics of human breathing and CFD boundary settings.