Computational Modeling of the COVID-19 Particle Spreading in the Airport Terminals

与卡尔加里机场管理局的Data and Analytics合作，该项目的目标是应用高保真计算建模方法来评估冠状病毒粒子可能在特定空间(例如机场航站楼或机舱)传播的程度。在这些环境中，空气流动模式非常复杂，经验关系很可能会超出其适用范围。所采用的计算框架可以准确地预测复杂受限空间中多相湍流的行为。特别是，不同的呼吸模式，例如打喷嚏、咳嗽和正常呼吸，将在机场航站楼等空间内模拟单个人和一群人。模型中还将考虑实际的空调系统，以预测周围空气中颗粒物的行为及其沉积。模拟将使我们能够检验假设，即当前的指导方针是否是对个体之间的安全距离的现实估计。数字框架将有助于确定最有可能积累颗粒物的地方，并可以提出建议，说明哪些表面需要更频繁地清洁。可以就如何安排工作人员(例如，在大门或安检点)以最大限度地减少感染的可能性提供指导方针。

In collaboration with Data and Analytics at the Calgary Airport Authority, the goal of this project is to apply high-fidelity computational modeling approach to assess the extent to which the coronavirus particles may spread through a given space (e.g. airport terminals or airplane cabins). In these environments the air flow patterns are very complex, and the empirical relations are likely will be outside the range of their applicability. The computational framework to be applied can accurately predict the behavior of multi-phase turbulent flows in complex confined spaces. In particular, different breathing modes, e.g. sneeze, cough and normal breathing, will be simulated from a single person and a group of people inside the spaces like airport terminals. The actual air conditioning systems will also be taken into account in the model in order to predict the behavior of the particles in the surrounding air and its deposition. The simulation will enable us to test the hypothesis of whether the current guidelines is a realistic estimate of a safe distance between the individuals. The numerical framework will help to identify the most likely places where the particles will accumulate, and recommendations could be made as to which surfaces need to be cleaned more often. The guidelines can be provided on how to place the staff members (e.g. at the gates or at the security check points) to minimize the likelihood of infection.