Behera Sachidananda, Bhardwaj Rajneesh, Agrawal Amit
Department of Mechanical Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India.
Phys Fluids (1994). 2021 Oct;33(10):101701. doi: 10.1063/5.0064104. Epub 2021 Oct 12.
We discuss the temporal evolution of a cough jet of an infected subject in the context of the spread of COVID-19. Computations were carried out using large eddy simulation, and, in particular, the effect of the co-flow (5% and 10% of maximum cough velocity) on the evolution of the jet was quantified. The Reynolds number (Re) of the cough jet, based on the mouth opening diameter () and the average cough velocity, is 13 002. The time-varying inlet velocity profile of the cough jet is represented as a combination of gamma-probability-distribution functions. Simulations reveal the detailed structure of cough jet with and without a co-flow for the first time, to the best of our knowledge. The cough jet temporal evolution is similar to that of a continuous free-jet and follows the same routes of instability, as documented for a free-jet. The convection velocity of the cough jet decays with time and distance, following a power-law variation. The cough jet is observed to travel a distance of approximately 1.1 m in half a second. However, in the presence of 10% co-flow, the cough jet travels faster and covers the similar distance in just 0.33 s. Therefore, in the presence of a co-flow, the probability of transmission of COVID-19 by airborne droplets and droplet nuclei increases, since they can travel a larger distance. The cough jet without the co-flow corresponds to a larger volume content compared to that with the co-flow and spreads more within the same range of distance. These simulations are significant as they help to reveal the intricate structure of the cough jet and show that the presence of a co-flow can significantly augment the risk of infection of COVID-19.
我们在新冠病毒传播的背景下讨论了感染个体咳嗽飞沫的时间演变。使用大涡模拟进行了计算，特别是量化了同向流（最大咳嗽速度的5%和10%）对飞沫演变的影响。基于口腔开口直径（）和平均咳嗽速度，咳嗽飞沫的雷诺数（Re）为13002。咳嗽飞沫随时间变化的入口速度剖面表示为伽马概率分布函数的组合。据我们所知，模拟首次揭示了有和没有同向流时咳嗽飞沫的详细结构。咳嗽飞沫的时间演变与连续自由射流相似，并遵循与自由射流相同的不稳定路径。咳嗽飞沫的对流速度随时间和距离衰减，遵循幂律变化。观察到咳嗽飞沫在半秒内传播约1.1米的距离。然而，在存在10%同向流的情况下，咳嗽飞沫传播得更快，在仅0.33秒内就能覆盖类似的距离。因此，在存在同向流的情况下，新冠病毒通过空气传播的飞沫和飞沫核传播的可能性增加，因为它们可以传播更远的距离。与有同向流的情况相比，没有同向流的咳嗽飞沫对应更大的体积含量，并且在相同的距离范围内扩散得更多。这些模拟很重要，因为它们有助于揭示咳嗽飞沫的复杂结构，并表明同向流的存在会显著增加新冠病毒感染的风险。
