Effect of Personalized Ventilation in Seat Armrest on Diffusion Characteristics of Respiratory Pollutants in Train Carriages

Liu, X.; Li, T.; Wu, S.; Zhang, J.

doi:10.47176/jafm.16.12.1953

Effect of Personalized Ventilation in Seat Armrest on Diffusion Characteristics of Respiratory Pollutants in Train Carriages

Document Type : Regular Article

Authors

State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu, China

10.47176/jafm.16.12.1953

Abstract

As one of the most important means of transportation, high-speed trains have a large capacity for carrying passengers. However, their narrow carriages can easily exacerbate the spread of respiratory diseases. Just like personalized ventilation in an airplane, ventilation in seat armrests of high-speed trains may increase comfort for passengers, but also influence the diffusion characteristics of respiratory pollutants. In this study, the effect of personalized ventilation in seat armrests, on the diffusion characteristics of respiratory pollutants in train carriages, is studied by means of the tracer gas method. Taking the ceiling air supply as the original ventilation system, comfortable temperature and pollutant diffusion characteristics of the personalized ventilation system, with 4 different air supply angles, are investigated. The 4 angles are 0°, 30°, 45° and 60°. When the personalized ventilation with the above 4 angles is adopted, the fluctuation amplitudes of pollutants in the passenger breathing zone are reduced by 15.84%, 19.27%, 19.76% and 19.68%, respectively, compared with the original ventilation system. It indicates that the sensible use of personalized ventilation can effectively reduce the passengers’ contaminant concentrations in the breathing zone, thereby reducing the possibility of cross-contamination between passengers. In addition, the use of the personalized ventilation system leads to a slight improvement in the thermal comfort and flow uniformity in the carriage. Based on the results, personalized air supply with an angle of 45° is advised for use in high-speed trains.

Keywords

Main Subjects

Computational Fluid Dynamics

References

Ai, Z. T., Mak, C. M., Gao, N. P., & Niu, J. L. (2020). Tracer gas is a suitable surrogate of exhaled droplet nuclei for studying airborne transmission in the built environment. Building Simulation, 13(3), 489-496. https://doi.org/10.1007/s12273-020-0614-5

Assaad, D. A., Ghali, K., & Ghaddar, N. (2019). Effect of flow disturbance induced by walking on the performance of personalized ventilation coupled with mixing ventilation. Build and Environment 160, 106217.1-106217.18. https://doi.org/10.1016/j.buildenv.2019.106217

Alain, M., Kamel, G., & Nesreen, G. (2015). Low-mixing coaxial nozzle for effective personalized ventilation. Indoor and Built Environment 24(2), 225-243. https://doi.org/10.1177/1420326X13508967

Barone, G., Buonomano, A., Forzano Cesare., & Palombo, A. (2020). Enhancing trains envelope - heating, ventilation, and air conditioning systems: A new dynamic simulation approach for energy, economic, environmental impact and thermal comfort analyses. Energy, 204. https://doi.org/10.1016/j.energy.2020.117833

Mboreha, C. A., Sun, J., Wang, Y., & Sun, Z. (2022). Airflow and contaminant transport in innovative personalized ventilation systems for aircraft cabins: A numerical study. Science and Technology for the Built Environment 28(4), 557-574. https://doi.org/10.1080/23744731.2022.2050632

Chen, Q. (1995). Comparison of different k-epsilon models for indoor air-flow computations. Numerical Heat Transfer, Part B, 28(3), 353-369. https://doi.org/10.1080/10407799508928838

Debnath, S., Saha, A. K., Siddheshwar, P. G., & Roy, A. K. (2018). On dispersion of a reactive solute in a pulsatile flow of a two-fluid model. Journal of Applied Fluid Mechanics, 12(3), 987-1000. https://doi.org/10.29252/jafm.12.03.29101

Elvire, K., Nesreen, G., Kamel, G., Douss A., & Saud, G. (2021). Effect of individually controlled personalized ventilation on cross-contamination due to respiratory activities. Build and Environment, 194. https://doi.org/10.1016/j.buildenv.2021.107719

Ghaddar, D., Itani, M., Ghaddar, N., Ghali, K., & Zeaiter, J. (2021). Model-based adaptive controller for personalized ventilation and thermal comfort in naturally ventilated spaces. Building Simulation, 14(6), 1757-1771. https://doi.org/10.1007/s12273-021-0783-x

Gupta, J. K., Lin, C. H., & Chen, Q. Y. (2009). Flow dynamics and characterization of a cough. Indoor Air, 19(6), 517-525. https://doi.org/10.1111/j.1600-0668.2009.00619.x

Gupta, J. K., Lin, C. H., & Chen, Q. Y. (2010). Characterizing exhaled airflow from breathing and talking. Indoor Air, 20(1), 31-39. https://doi.org/10.1111/j.1600-0668.2009.00623.x

Hachem, M., Saleh, N., Paunescu, A., Momas, I., Bensefa-Colas, L. (2019). Exposure to traffic air pollutants in taxicabs and acute adverse respiratory effects: A systematic review. Science of the Total Environment, 693, 133439. https://doi.org/10.1016/j.scitotenv.2019.07.245

Liu, H., He, S. D., Shen, L., & Hong, J. R. (2021). Simulation-based study of COVID-19 outbreak associated with air-conditioning in a restaurant. Physics of Fluids 33(2), 023301. https://doi.org/10.1063/5.0040188

Izadyar, N., & Miller, W. (2022). Ventilation strategies and design impacts on indoor airborne transmission: A review. Building and Environment, 218, 109158. https://doi.org/10.1016/j.buildenv.2022.109158

Li, X. P., Niu, J. L., & Gao, N. P. (2011). Spatial distribution of human respiratory droplet residuals and exposure risk for the co-occupant under different ventilation methods. HVAC & R Research, 17(4), 432-445. https://doi.org/10.1080/10789669.2011.578699

Li, X. P., Niu, J. L., & Gao, N. P. (2013). Co-occupant’s exposure to exhaled pollutants with two types of personalized ventilation strategies under mixing and displacement ventilation systems. Indoor Air, 23(2), 162-171. https://doi.org/10.1111/ina.12005

Li, X. D., Shang, Y. D., Yan, Y. H., Yang, L., & Tu, J. Y. (2018). Modelling of evaporation of cough droplets in inhomogeneous humidity fields using the multi-component Eulerian-Lagrangian approach. Building and Environment, 128, 68-76. https://doi.org/10.1016/j.buildenv.2017.11.025

Li, T., Wu, S. B., Yi, C., Zhang, J. Y., & Zhang, W. H. (2022). Diffusion characteristics and risk assessment of respiratory pollutants in high-speed train s. Journal of Wind Engineering and Industrial Aerodynamics, 222. https://doi.org/10.1016/j.jweia.2022.104930

Li, M. X., Zhao, B., Tu, J. Y., & Yan, Y. H. (2015). Study on the carbon dioxide lockup phenomenon in aircraft cabin by computational fluid dynamics. Building Simulation 8(4), 431-441. https://doi.org/10.1007/s12273-015-0217-8

Mangili, A., & Gendreav, M. A. (2005). Transmission of infectious diseases during commercial air travel. The Lancet (North American Edition), 365(9463), 989-996. https://doi.org/10.1016/S0140-6736(05)71089-8

Mao, N., Yu, H., Zhuang, J. J., & Song, M. J. (2022). Numerical study on supply parameters' influence on ventilation performance of a personalized air conditioning system for sleeping environments. Journal of Thermal Analysis and Calorimetry, 147(20), 11331-11343. https://doi.org/10.1007/s10973-022-11332-5

Mechighel, F., Armour, N., & Dost, S. (2021). Modeling of the effect of the presence of a free surface on transport structures and mixing during the dissolution process of silicon into germanium melt. Journal of Thermal Analysis and Calorimetry, 146(1), 61-91. https://doi.org/10.1007/s10973-020-09957-5

Melikov, A. K. (2004). Personalized ventilation. Indoor Air, 14(7), 157-167. https://doi.org/10.1111/j.1600-0668.2004.00284.x

Melikov, A. K., Ivanova, T., & Stefanova, G. (2012). Seat headrest-incorporated personalized ventilation: Thermal comfort and inhaled air quality. Build and Environment, 47(1), 100-108. https://doi.org/10.1016/j.buildenv.2011.07.013

Pesic, D. J., Zigar, D. N., Anghel, I., & Glisovic, S. M. (2016). Large eddy simulation of wind flow impact on fire induced indoor and outdoor air pollution in an idealized street canyon. Journal of Wind Engineering and Industrial Aerodynamics, 155, 89-99. https://doi.org/10.1016/j.jweia.2016.05.005

Posner, J. D., Buchanan, C. R., & Dunn-Rankin, D. (2003). Measurement and prediction of indoor air flow in a model room. Energy and Buildings, 35(5), 515-526. https://doi.org/10.1016/S0378-7788(02)00163-9

Razvan, M., Georgescu, M. R., Meslem, A., Nastase, I., & Bode, F. (2021). Personalized ventilation solutions for reducing CO2 levels in the crew quarters of the International Space Station. Build and Environment, 204. https://doi.org/10.1016/j.buildenv.2021.108150

Sen, N. (2021). Transmission and evaporation of cough droplets in an elevator: Numerical simulations of some possible scenarios. Physics of Fluids, 33(3), 033311. https://doi.org/10.1063/5.0039559

Shih, T. H., Zhu, J., & Lumley, J. L. (1995). A new reynolds stress algebraic equation model. Computer Methods in Applied Mechanics and Engineering, 125(1-4), 287-302. https://doi.org/10.1016/0045-7825(95)00796-4

Sherman, M. H. (1990). Tracer-gas techniques for measuring ventilation in a single zone. Build and Environment, 25(4), 365-374. https://doi.org/10.1016/0360-1323(90)90010-O

Wang, H. T., Lin, M. D., & Chen, Y. (2014). Performance evaluation of air distribution systems in three different china railway high-speed train cabins using numerical simulation. Building Simulation, 7(6), 629-638. https://doi.org/10.1007/s12273-014-0168-5

Wei, J. J., & Li, Y.G. (2015). Enhanced spread of expiratory droplets by turbulence in a cough jet. Building and Environment, 93(P2), 86-96. https://doi.org/10.1016/j.buildenv.2015.06.018

Wu, S. B., Li, T., Yi, C., Zhang, J. Y., & Zhang, W. H. (2022). Effects of exhaust methods on air distribution and respiratory pollutants diffusion characteristics in high-speed train compartments (in Chinese). Sci Sin Tech, 52. https://doi.org/10.1360/SST-2021-0363

Xu, C. W., Wei, X. X., Liu, L., Su, L., Liu, W. B., Wang, Y., Nielsen, P. V. (2020). Effects of personalized ventilation interventions on airborne infection risk and transmission between occupants. Build and Environment 180, 107008. https://doi.org/10.1016/j.buildenv.2020.107008

Xu, C. W., Nielsen, P. V., Liu, L. L., Jensen, R. L., & Gong, G. C. (2018). Impacts of airflow interactions with thermal boundary layer on performance of personalized ventilation. Build and Environment, 135, 31-41. https://doi.org/10.1016/j.buildenv.2018.02.048

Xu, J. C., Fu, S., & Chao, C. Y. H. (2021). Performance of airflow distance from personalized ventilation on personal exposure to airborne droplets from different orientations. Indoor and Built Environment, 30(10), 1643-1653. https://doi.org/10.1177/1420326X20951245

Xui, J. C., Fu, S. C., & Christopher, Y. H C. (2021). Performance of airflow distance from personalized ventilation on personal exposure to airborne droplets from different orientations. Indoor and Built Environment, 30(10), 1643-1653.

Yang, C. Q., Yang, X. D., & Zhao, B. (2015). The ventilation needed to control thermal plume and particle dispersion from manikins in a unidirectional ventilated protective isolation room. Building Simulation, 8(5), 551-565. https://doi.org/10.1007/s12273-014-0227-6

Zhang, L., & Li, Y. G. (2021). Dispersion of coughing droplets in a fully-occupied high-speed rail cabin. Build and Environment, 47(1), 58-66. https://doi.org/10.1016/j.buildenv.2011.03.015

Zhang, T. F., Li, P. H., & Wang, S. G. (2012). A personal air distribution system with air terminals embedded in chair armrests on commercial airplanes. Build and Environment, 47, 89-99. https://doi.org/10.1016/j.buildenv.2011.04.035

Zhou, Y., Wang, M. Y., Wang, M. N., & Wang, Y. (2018). Predictive accuracy of Boussinesq approximation in opposed mixed convection with a high-temperature heat source inside a building. Building and Environment, 144, 349-356. https://doi.org/10.1016/j.buildenv.2018.08.043