Journal Search Engine
Search Advanced Search Adode Reader(link)
Download PDF Export Citaion korean bibliography PMC previewer
ISSN : 2288-9167(Print)
ISSN : 2288-923X(Online)
Journal of Odor and Indoor Environment Vol.18 No.2 pp.131-139
DOI : https://doi.org/10.15250/joie.2019.18.2.131

Numerical analysis of droplets exhaled by train cabin passengers

Sangwon Ko1, Wootae Jeong1, Duckshin Park1, Soon-Bark Kwon1,2*
1Transportation Environmental Research Team, Korea Railroad Research Institute
2R&D Center, DAP Inc.
Corresponding author Tel : +82-31-460-5375 E-mail : sbkwon@krri.re.kr, ksb@dapair.co.kr
20/03/2019 20/05/2019 24/06/2019

Abstract


Using computational fluid dynamics (CFD), this study simulated the air supply and exhaust conditions inside KTXSancheon train cabin to analyze the airflow, velocity, temperature, and residence time distributions. Based on the analyzed airflow in the cabin, the trajectory properties of droplets with various diameters exhaled from a passenger in a specific seat were analyzed. In the train cabin, forced airflow was formed by the operation of an air conditioning unit, while air stagnation occurred through spinning vortices at the front and rear where there were no floor outlets. Droplet particles ≤36 μm in diameter were dispersed throughout the cabin following the airflow generated by the air conditioning unit. The degree of dispersion differed according to the passenger seat location. In addition, the expelled droplets were mostly deposited on the surfaces of passenger bodies, seats, and floor. The ratio of deposited droplets to suspended droplets was increased with increasing droplet size. Further, the CFD study allowed the prediction of the possibility of exposure to exhaled droplets by estimating the dispersion and deposition properties of droplets released from a passenger in a specific seat. This study can be utilized to adjust the operation of air conditioning units and encourage the installation of air-purifying units to minimize secondary infections.



수치해석을 이용한 철도차량 승객의 토출 비말입자 거동분석

고 상원1, 정 우태1, 박 덕신1, 권 순박1,2*
1한국철도기술연구원 교통환경연구팀
2㈜디에이피

초록


    © Korean Society of Odor Research and Engineering & Korean Society for Indoor Environment. All rights reserved.

    1. Introduction

    Droplets expelled through coughing or sneezing by someone with a cold or infectious respiratory illness can increase the incidence of infection through direct personto- person transfer of droplets, inhalation of droplets suspended in the air, or contact with droplets deposited on a surface (Kwon et al., 2012;Kwon et al., 2013;Bourouiba et al., 2014). Droplet transmission generally occurs for an infecter and infectee in close proximity, because relatively large particles are deposited more quickly. However, airborne transmission occurs through the dispersion of expelled small droplets or droplet nuclei of a few micrometers or less in size, formed via evaporation. Such airborne droplets remain suspended in the air longer and travel further on indoor airflow. After the reported dispersion of severe acute respiratory syndrome (SARS) from an infected person to other passengers inside an aircraft during the SARS outbreak in 2003 (Olsen et al., 2003), it was confirmed that airborne transmission can occur through the dispersion of droplets by indoor airflows, not only through droplet transmission between persons in close proximity (Wong et al., 2004;Yu et al., 2004).

    Because airborne transmission usually occurs through respiratory activities, many studies have analyzed expelled droplet size distributions (Duguid, 1946;Papineni and Rosenthal, 1997;Chao et al., 2009;Edwards et al., 2004;Fabian et al., 2008;Han et al., 2013), coughing fluid dynamics (Bourouiba et al., 2014;Kwon et al., 2012;Chao et al., 2009), and trajectories of particles expelled through coughing or sneezing (Kwon et al., 2013;Yan et al., 2009;Mazumdar and Chen, 2009;Zhu et al., 2005;Sze et al., 2008;Sze et al., 2009). Fluid dynamics analyses have visualized the velocity fields of coughing and presented average coughing velocities of 11.7 m/s (Chao et al., 2009) and 13.0 m/s (Kwon et al., 2012). Numerical analysis of droplet trajectory revealed that particles of 50–200 μm were greatly affected by gravity, while droplets of ≤30 μm were greatly affected by indoor airflow (Kwon et al., 2013;Yan et al., 2009;Mazumdar and Chen, 2009;Zhu et al., 2005). Experimental studies of expiratory aerosols in indoor mockups also showed that indoor airflow and coughing orientation significantly influenced the dispersion properties of exhaled particles (Sze et al., 2008;Sze et al., 2009).

    Indoor airflow, mainly determined by the ventilation type, affects the transport characterization of expelled droplets. Thus, the analysis of the trajectory properties of expelled droplets is useful for predicting the exposure risk of other people to respiratory pathogens from an infected person and for proposing ventilation and air purification methods to minimize secondary infection. Moreover, the analysis of the deposition patterns of nonexhausted droplet particles can facilitate the utilization of antibacterial surface coatings, as well as the selection of ventilation methods to minimize exposure through droplet contact. This study used a computational fluid dynamics (CFD) program to simulate the airflow patterns formed by an air conditioning unit operating inside a cabin on KTX-Sancheon by assuming that the position of expelled droplets was determined by the location of the infected passenger’s seat. This study also predicted the trajectory properties and deposition positions according to the diameter and position of discharged droplets.

    2. Research Method

    2.1 Numerical analysis

    In this study, a cabin with 48 seats (four columns of 12 rows) on the KTX-Sancheon train was selected for analysis. The shape and analysis grids of the cabin are modeled as shown in Fig. 1, assuming a cabin filled with passengers. Fig. 1(a) to 1(c) show the grids of the cabin, floor, seats, and passengers; the grid density is higher around the air supply inlets and exhaust outlets that affect indoor airflow. A total of 20 million grid elements were configured using the Integrated Computer Engineering and Manufacturing (ICEM) CFD program (USA) for analysis. In addition to modeling the airflow pattern in the cabin, the analysis was intended to deduce the trajectory properties of droplet particles, assuming that they were exhaled by the coughing of an infected passenger in a specific seat. Moreover, a deposition distribution diagram of exhaled droplets was simulated to determine the possibility of contact with droplets deposited in the cabin by passengers in other seats. The body, the seat and armrests, the back of the seat in front, and the floor are selected as surfaces on which a passenger could come into touch infected droplets, as shown in Fig. 1(d). The deposition patterns of particles not exhausted by the heating, ventilation, and air conditioning (HVAC) system were characterized according to droplet diameter and generation location.

    2.2 Boundary conditions

    The HVAC system is mounted on the bottom of the vehicle, and air is supplied and exhausted at 55 m3/min. As seen in Fig. 2, air is supplied through 12 line inlets below the windows (Fig. 2(a)) and 12 side inlets (Fig. 2(b)) next to the seats, with an inlet layout having bilateral symmetry. Air is exhausted out through 10 side outlets (Fig. 2(c)) and six floor outlets (Fig. 2(d)). The locations of the 10 side outlets and six floor outlets differ from cabin to cabin. If the 10 side outlets are located on the side of column A, six floor outlets are located between columns C and D, yielding an asymmetrical structure. This analysis modeled a cabin with side outlets next to seats 1A, 2A, 3A, 5A, 6A, 7A, 8A, 10A, 11A and 12A.

    To determine the boundary conditions, the area of each inlet and outlet in addition to the air velocity at each supply inlet and exhaust outlet was measured to calculate the quantity of flow in the cabin. The ratio of measured air flows supplied through the line and side inlets was approximately 7:1, while that of measured air flows exhausted through the side and floor outlets was approximately 1:4.5. Because the total air supply and total air exhaust were balanced at 55 m3/min, the flow ratios of the supply inlets and exhaust outlets were employed as the boundary conditions. To set heating boundary conditions, a temperature of 37°C was used for the neck and face, as those parts of the body are exposed to the atmosphere, and a temperature of 25°C was used for the rest of the clothed body. The supplied air temperature was set to 25°C measured in the spring (May). The commercial program ANSYS CFX (Ver. 17.0, USA) with the shear stress transport (SST) turbulence model was used for analysis.

    3. Results and discussion

    3.1 Airflow distribution according to air supply and air exhaust conditions

    Fig. 3 shows the airflow pattern, velocity, temperature and residence time distributions in the major cross-sections of the KTX-Sancheon cabin under the air supply and exhaust conditions. The airflow distribution (Fig. 3(a)) begins at the line and side inlets and shows forced airflow from the inlets and outlets, rather than natural convective airflow. As seen by the airflow distribution in Fig. 3(a), air from the tops of the left and right seats flows to the bottoms of the seats on the opposite side of the center aisle; thus, it can be inferred that particles discharged from seats in rows A and B are dispersed to the seats in rows C and D and vice versa. As in the airflow distribution, the velocity distribution reveals the forced air current from inlets and outlets and the air flowing upward along the cabin side wall (Fig. 3(b)). The average air velocity inside the cabin is 0.17 m/s with a maximum velocity of up to 3.73 m/s near the inlets and outlets. Fig. 3(c) shows the temperature distribution inside the cabin. The average temperature is maintained at 25.2°C when the HVAC system is in operation. However, because the shelves installed in the upper section of the cabin interrupt airflow, the areas below where the passengers are seated show slightly higher temperatures. The fluid residence time also presents a fluid pattern along the wall attributed to the forced current. The average residence time of air inside the cabin is 78 sec. However, this is increased to 240 sec because of stagnated air from the rotating vortex formed in the area of seated passengers as well as in the front and rear of the cabin where no floor outlets are located.

    3.2 Dispersion characteristics of exhaled droplets

    The droplet diameters observed in measurements of actual coughing droplet distributions were used to analyze the trajectory properties (Chao et al., 2009). In addition to the droplet particles of 3, 36, and 87.5 μm described in the paper, particles with diameters of 6, 12, 20, 28, 45, 62.5, and 112.5 μm were also simulated. Assuming that the quantity of collected particles was small enough to avoid affecting the total flow, the trajectory properties were analyzed according to a one-way coupling method using a particle tracking technique.

    For the analysis of droplet trajectory and the exposure of other passengers according to the location of the seat of the infected passenger, i.e., the location of exhaled droplet generation, this study established three scenarios, as presented in Fig. 4. The cabin is divided into the three sections of front, center, and rear. Considering the positions of inlets and outlets that affect airflow inside the cabin, seat 11C, which is far from side and floor outlets (Case 1), seat 7B, which is located between a floor outlet and the aisle (Case 2), and seat 3A, which is near a side inlet and outlet (Case 3), are selected as the points of droplet generation. One thousand particles of each diameter were exhaled to analyze the particle trajectories and distribution deposited on the surfaces where a passenger would potentially contact with infected drop-lets as shown in Fig. 1(d).

    Although the droplet trajectory differs with the seat location where droplets are expelled, the analysis shows that droplets of 3–36 μm are generally dispersed along the airflow throughout a large area, those of 36–45 μm are deposited on specific nearby passengers because of airflow and gravity, and those of ≥62.5 μm are deposited near the discharge location because of gravity. To track the droplet particles according to the location of the expelled droplet source, Fig. 5 shows the representative trajectory and concentration of 3-μm droplets. For the droplet source located at 11C, a wide high-concentration distribution from seat 11C to the seat behind is observed (Fig. 5(a)). As seen in Fig 3d, the retention time is relatively long in the front of the cabin, and particles float more widely along the indoor current as there is no floor outlet with a larger flow than the side outlet. At seat 7B located in the middle and beside the aisle, the dispersion of droplets to the front and back is smaller than that for droplets generated at seats 3A and 11C, because of the existence of nearby floor outlets (Fig. 5(b)). The 3-μm droplets exhaled from seat 3A travel upward along the wall and shelf and are dispersed to other seats because of the downward airflow formed on the opposite side (Fig. 5(c)). The analysis of different sized droplets showed that those of ≤36 μm followed a pattern similar to that of 3-μm droplets, while those of >36 μm showed lower dispersion and shorter travel ranges.

    3.3 Deposition characteristics of exhaled droplets

    The distribution of droplets deposited on surfaces of interest was analyzed according to the generation location and droplet diameter, as shown in Fig. 6. The deposition pattern (black dots) of 3-μm droplets exhaled by the passenger in seat 11C (case 1) shows that most depositions occur behind the passenger (Fig. 6(a)), as indicated in the particle trajectory described above (Fig. 5(a)). Droplets of 36 μm are also mostly deposited behind seat 11C, with concentrations around seats 10B and 10C (Fig. 6(b)). However, larger droplets such as those of 87.5 μm in diameter are deposited on and near seat 11C (Fig. 6(c)). For seat 7B (blue dots) in case 2, 3-μm droplets are dispersed to the aisle and seats in columns C and D (Fig. 6(a)), probably because of the downward airflow from the tops of the seats in columns A and B to the bottoms of the seats in columns C and D, as shown in Fig. 3(a). It is noteworthy that droplets of 36 μm exhaled from seat 7B are mostly deposited near the passenger (Fig. 6(b)), unlike those exhaled from seats 11C and 3A, which are clearly dispersed along the airflow inside the cabin. This is attributed to the floor outlet near seat 7B. Droplets of 87.5 μm are mostly deposited near the seat from which they are generated (Fig. 6(c)). Like the trajectory shown in Fig. 5(c), 3-μm droplets sized expelled from seat 3A (red dots) in case 3 are dispersed to seats in columns C and D on the opposite side of the aisle (Fig. 6(a)). Droplets of 36 μm are mostly deposited on the passenger’s seat (3A), the next seat (3B) and the aisle, while those of 87.5 μm are mostly deposited on seat 3A (Fig. 6(b) and 6(c)).

    As mentioned above, the smaller droplet particles (3 μm) are dispersed based on the impact of indoor airflow in all three seats and generally concentrated near the center of the cabin. Larger droplets (87.5 μm) are deposited near the seat from which they are discharged. Dispersion to other seats and deposition patterns differ according to the seat location.

    3.4 Quantitative analysis of deposition rate

    The ratio of deposited to total discharged droplets according to droplet diameter is shown in Fig. 7. The deposition rate for droplets of ≥45 μm is ≥98% for all three cases. This is because, as mentioned above, the larger droplets are mostly deposited near and around the exhaling passenger, rather than being dispersed or exhausted. Thus, the total deposition proportion is affected more by droplet size than by the location. On the other hand, ≥50% of droplets of ≤10 μm are suspended inside the cabin. Specifically, more droplets discharged from seats 7B and 11C remain in the air than those discharged from seat 3A. Thus, to minimize the risk of spreading infection to other passengers through airborne or contact transmission, utilization of air purification systems and antibacterial surface coatings (Jeong et al., 2018) may be effective, along with adjusting the airflow from the air conditioning unit and rearranging seats for symptomatic passengers. With an air purification system, a simulation study on the mitigation pattern of dispersed droplets according to air flow, purifier performance, and operating time may also facilitate plans to reduce passengers’ exposure to the expelled droplets (Fu et al., 2001).

    3.5 Overall deposition pattern

    Although the three seats selected for analysis in this study represent important points in the cabin, they provide limited information concerning all possible situations in all seats. As such, an overall analysis was performed with droplets expelled from all seats in the cabin simultaneously. Fig. 8 shows the locations and amounts of deposition for 3-μm droplets are generated from all seats. Deposition is higher at the center and upper right section of the cabin, while lower deposition is observed in the rows 1, 11, and 12, which are near the edge of the cabin.

    Various infection path scenarios can be evaluated using the methodology of trajectory analysis of exhaled droplets applied in this study. To reduce secondary infection, these results can also be utilized as references for predicting the exposure risk of occupants according to the airflow conditions, seat locations, and exhaled droplet sizes. Furthermore, the initial diameters of the droplets simulated in this study actually decrease during real dispersion, as the droplets exhaled by a passenger sneezing quickly evaporate under air exposure (Xie et al., 2007). Therefore, the trajectory properties of large drop- lets of dozens of micrometers in diameter are expected to resemble the pattern of small droplets, i.e., those ≤36 μm, as analyzed in this study. Moreover, although this study did not closely consider the occurrence of infection, it is noted that infection does not occur simply through the inhalation of or contact with infected droplets. Thus, the pathogen activity and probability of infection for each passenger should also be considered (Morawska, 2006).

    4. Conclusions

    This study demonstrated the trajectories of particles exhaled through coughing or sneezing from passengers seated in specific locations in KTX-Sancheon train cabin using the CFD. We found that droplet particles of ≤36 μm in diameter were dispersed throughout the cabin following the airflow generated by the air conditioning unit; the degree of dispersion differed according to the passenger’s seat location. However, larger particles of >36 μm were mostly deposited near the source location because of gravity. As shown in the overall deposition pattern, the exhaled droplets were mainly deposited in the middle and right upper section of the cabin, while lower deposition proportions were observed at the cabin edges. The developed methodology of trajectory analysis can be applied to predict the possibility of exposure to exhaled droplets as well as various infection path scenarios by estimating the dispersion and deposition properties of such droplets. In addition, this study can be used to adjust the operation of air conditioning units and encourage the installation of air purification units to minimize secondary infections.

    Acknowledgements

    This research was supported by a grant from the R&D Program of the Korea Railroad Research Institute, Republic of Korea.

    Figure

    JOIE-18-2-131_F1.gif

    Mesh regions of (a) KTX-Sancheon cabin, (b) floor, and (c) passengers and seats; (d) surface area of aerosol deposition for each passenger.

    JOIE-18-2-131_F2.gif

    Locations of air supply inlets and exhausts outlets in a KTX-Sancheon cabin: (a) and (b) show line and side inlets, (c) and (d) show side and floor outlets.

    JOIE-18-2-131_F3.gif

    Distribution properties of (a) airflow (front view, seats D–A from left), (b) velocity, (c) temperature, and (d) residence time in the simulated KTX-Sancheon cabin under the set boundary conditions.

    JOIE-18-2-131_F4.gif

    Seat locations of droplet generation sources for three scenarios.

    JOIE-18-2-131_F5.gif

    Trajectory of 3-μm droplets released from generation sources at seats (a) 11C (case 1), (b) 7B (case 2), and (c) 3A (case 3) in simulated KTX-Sancheon cabin.

    JOIE-18-2-131_F6.gif

    Deposition pattern maps of (a) 3-μm droplets, (b) 36-μm droplets, (c) 87.5-μm droplets released from seat 11C (Case 1, black), seat 7B (Case 2, blue), and seat 3A (Case 3, red) in simulated KTX-Sancheon cabin.

    JOIE-18-2-131_F7.gif

    Total deposition rates on passengers, seats, and floor by particle size.

    JOIE-18-2-131_F8.gif

    Deposition pattern map of 3-μm droplets concurrently released from all seats in the KTX-Sancheon cabin.

    Table

    Reference

    1. Bourouiba, L. , Dehandschoewercker, E. , Bush, J. W. M.,2014. Violent expiratory events: on coughing and sneezing. Journal of Fluid Mechanics 745, 537-563.
    2. Chao, C. Y. H. , Wan, M. P. , Morawska, L , Johnson, G. R. , Ristovski, Z. D. Hargreaves, M., Mengersen, K., Corbett, S., Li, Y., Xie, X., Katoshevski, D., 2009. Characterization of expiration air jets and droplet size distributions immediately at the mouth opening. Journal of Aerosol Science 40(2), 122-133.
    3. Duguid, J. P. ,1946. The size and the duration of air-carriage of respiratory droplets and droplet-nuclei. The Journal of Hygiene 44(6), 471-479.
    4. Edwards, D. A. , Man, J. C. , Brand, P., Katstra, J. P., Sommerer, K. H., Stone, A., Nardell, E., Scheuch G.,2004. Inhaling to mitigate exhaled bioaerosols. Proceedings of the National Academy of Sciences of the United States of America 101(50), 17383-17388.
    5. Fabian, P., McDevitt, J. J., DeHaan, W. H., Fung, R. O. P., Cowling, B. J., Chan, K. H. Leung, G. M., Milton, D. K.,2008. Influenza virus in human exhaled breath: an observational study. PLoS ONE 3(7), e2691.
    6. Fu, W. S. , Chen, S. F. , Yang, S. J. ,2001. Numerical simulation of effects of moving operator on the removal of particles in cleanroom. Aerosol Air Quality Research 1(1), 37-45.
    7. Han, Z. Y. , Weng, W. G. , Huang, Q. Y. ,2013. Characterization of particle size distribution of the droplets exhales by sneeze. Journal of The Royal Society Interface 10(88), 20130560.
    8. Jeong, Y. , Thuy, L. T. , Ki, S. H. , Ko, S. , Kim, S. , Cho, W. K. , Choi, J. S. , Kang, S. M. ,2018. Multipurpose antifouling coating of solid surfaces with the marine-derived polymer fucoidan. Macromolecular Bioscience 18(10), 1800137.
    9. Kwon, S. B., Park, J., Jang, J., Cho, Y. Park, D. S., Kim, C., Bae, G. N., Jang, A.,2012. Study on the initial velocity distribution of exhaled air from coughing and speaking. Chemosphere 87(11), 1260-1264.
    10. Kwon, S. B. , Song, J. H. , Cho, Y. M. , Jeong, W. T. , Park, D. S. ,2013. Effect of Ventilation type on the trajectory of coughed particles in a hospital ward. Particle and Aerosol Research 9(2), 59-67. (in Korean with English abstract)
    11. Mazumdar, S. , Chen, Q. ,2009. A one-dimensional analytical model for airborne contaminant transport in airliner cabins. Indoor Air 19(1), 3-13.
    12. Morawska, L. ,2006. Droplet fate in indoor environments, or can we prevent the spread of infection? Indoor Air 16(5), 335-347.
    13. Olsen, S. J., Chang, H. L., Cheung, T. Y. Y., Tang, A. F. Y., Fisk, T. L., Ooi, S. P. L. Kuo, H.W., Jiang, D. D. S., Chen,K. T., Lando, J., Hsu, K. H., Chen, T. J., Dowell, S. F.,2003. Transmission of the severe acute respiratory syndrome on aircraft. The New England Journal of Medicine 349(25), 2416-2422.
    14. Papineni, R. S. , Rosenthal. F. S. ,1997. The size distribution of droplets in the exhales breath of healthy human subjects. Journal of Aerosol Medicine 10(2), 105-116.
    15. Sze To, G. N. , Wan, M. P. , Chao, C. Y. H. , Fang, L. , Melikov, A. ,2009. Experimental study of dispersion and deposition of expiratory aerosols in aircraft cabins and impact on infectious disease transmission. Aerosol Science and Technology 43(5), 466-485.
    16. Sze To, G. N. , Wan, M. P. , Chao, C. Y. H. , Wei, F. , Yu, S. C. T. , Kwan, J. K. C. ,2008. A methodology for estimating airborne virus exposures in indoor environments using the spatial distribution of expiratory aerosols and virus viability characteristics. Indoor Air 18(5), 425-438.
    17. Wong, T. W. , Lee, C. K. , Tam, W. J. , Lau, T. , Yu, T. S. , Lui, S. F. , Chan, P. K. , Li, Y. , Bresee, J. S. , Sung, J. J. , Parashar, U. D. ,2004. Cluster of SARS among medical students exposed to single patient, Hong Kong. Emerging Infectious Diseases 10(2), 269-276.
    18. Xie, X. , Li, Y. , Chwang, A.T.Y., Ho, PL. , Seto, WH. ,2007. How far droplets can move in indoor environmentsrevisiting the Wells evaporation-falling curve. Indoor Air 17(3), 211-215.
    19. Yan, W. , Zhang, Y. , Sun, Y. , Li, D. ,2009. Experimental and CFD study of unsteady airborne pollutant transport within and aircraft cabin mock-up. Building and Environment 44(1), 34-43.
    20. Yu, I. T. , Li, Y. , Wong, T. W. , Tam, W. , Chan, A. T. , Lee, J. H. , Leung, D. Y. , Ho, T. ,2004. Evidence of airborne transmission of the severe acute respiratory syndrome virus. The New England Journal of Medicine 350(17), 1731-1739.
    21. Zhu, S. , Kato, S. , Yang, J. H. ,2005. Study on transport characteristics of saliva droplets produced by coughing in a calm indoor environment. Building and Environment 41(12), 1691-1702.