High-fidelity modeling of the drying kinetics, lifetimes, and trajectories of saliva droplets

到目前为止，对唾液液滴的干燥和扩散的评价都是采用简单的物理模型。这些模型支持了一个关键结论，即携带最多病毒副本的大飞沫导致了大多数Covid感染。这些大液滴沉淀得很快，所以只要我们和其他人保持两米的距离，就不会有危险。然而，自2020年11月以来封锁期间德国的高感染人数意味着这些假设是不合理的。相反，大液滴可能会干燥成小颗粒，这些颗粒足够轻，可以通过空气传播很远的距离，并导致病毒的间接传播。由于病毒副本不会蒸发，这些小颗粒可能是最危险的。在以前的项目中，我们开发了液滴蒸发和颗粒形成的先进数值模型。此外，我们还开发了紊流中液滴和颗粒传输的CFD工具。在这个项目中，我们将把现有的模型用于唾液干燥，并将它们组装成一个工具。该工具反映了详细的液滴干燥动力学，包括由于溶质而改变的蒸发速率和在液滴表面形成固体层。这种方法优于经典的d平方模型，可以预测可能的空心粒子。我们与Lund大学的Berrocal教授合作，他拥有独特的专业知识和世界领先的喷雾成像实验室之一。Berrocal教授使用高检测灵敏度和空间分辨率的成像技术，在一个人说话、咳嗽或打喷嚏时，同时测量液滴的数量、大小和速度。根据这些实验数据，我们将为模拟房间内的病毒传播生成准确的输入条件。这种详细的模拟将有助于更好地理解唾液液滴干燥动力学和病毒在特定情况下的传播。该项目的结果可能会导致对Covid防护指南的重新评估，特别是两米距离规则。因此，我们有助于管理当前和未来的大流行病。

So far, simple physical models are used to evaluate the drying and spreading of saliva droplets. These models support the critical conclusion that large droplets, which carry most viral copies, cause most Covid infections. These large droplets settle fast, so there is no danger as long as we keep a distance of two meters to other persons. However, the high number of infections in Germany during the lockdown since November 2020 implies that these assumptions are not justified. Instead, large droplets might dry into small particles which are light enough to be transported airborne over large distances and cause indirect virus transmission. Since the viral copies do not evaporate, these small particles might be the most dangerous ones. In previous projects, we have developed advanced numerical models for droplet evaporation and particle formation. Also, we developed a CFD tool for the transport of droplets and particles by turbulent airflow. In the proposed project, we will adapt the existing models to drying saliva and assemble them into one tool. This tool reflects the detailed droplet drying kinetics, including modifying the evaporation rate due to the solutes and forming a solid layer on the droplet surface. Such an approach is superior to the classical D-square model and will predict possible hollow particles. We collaborate with Prof. Berrocal (Lund University), who has unique expertise and one of the world-leading spray imaging laboratories. Prof. Berrocal provides simultaneous measurements of the droplet number, size, and velocity when a person is speaking, coughing, or sneezing, using imaging techniques of high detection sensitivity and spatial resolution. From this experimental data, we will generate accurate input conditions for our simulations of the virus transmission in a room. Such detailed simulations will lead to a better understanding of the saliva droplet drying kinetics and the virus transmission in specific situations. This project's results can lead to the re-evaluation of Covid protection guidelines, especially the two meters distancing rule. Hence, we contribute to managing the current and future pandemics.