Numerical analysis of airflow dynamics generated by human coughing based on PIV experimental results
Numerical analysis of airflow dynamics generated by human coughing based on PIV experimental results
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发表时间：
2021
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通讯作者：
PhD Ryozo Ooka;PhD Hideki Kikumoto;PhD Wonseok Oh;PhD Mengtao Han
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作者：
PhD Ryozo Ooka;PhD Hideki Kikumoto;PhD Wonseok Oh;PhD Mengtao Han
呼吸道感染是通过人类咳嗽、打喷嚏和说话产生的飞沫和飞沫核传播的。飞沫和飞沫核与气流同时从口腔中出来，它们的扩散特征对于了解感染的传播途径很重要。通过数值分析了解飞沫的弥散特征以及飞沫核的弥散和感染途径至关重要。本研究旨在提供计算流体动力学（CFD）模型的边界条件，以确认基于粒子图像测速（PIV）实验结果的人类咳嗽CFD分析的预测准确性。人体咳嗽产生气流的边界条件口腔投影面积假设为椭圆形，长轴长度为43.2 mm（1.7 in），长短轴之比为4。由于CFD模型中口腔边界条件对应的气流速度无法直接从PIV结果中推导出来，因此通过引入校正因子来分析时序气流分布，与实验结果误差最小的边界条件为反推导出来。因此，与实验中获得的整体平均值相比，通过 CFD 分析咳嗽产生的气流可以以 0.38–0.42 m/s (1.25–1.38 ft/s) 的 RMSE 重现。本研究提供了详细的建模技术和数值模拟的边界条件，用于分析人类咳嗽产生的气流特性。此外，通过额外测量飞沫和飞沫核的尺寸分布并引入拉格朗日分析，预计可以通过CFD分析来预测人类咳嗽引起的感染风险和途径。
Respiratory infections are transmitted by droplets and droplet nuclei generated by human coughing, sneezing, and talking. Droplets and droplet nuclei come out of the mouth simultaneously with airflow, and their dispersion characteristics are important to understand the transmission route of infection. It is crucial to understand the dispersion characteristics of droplets and droplet nuclei dispersion and infection routes through numerical analysis. The present study aims to provide boundary conditions of the computational fluid dynamics (CFD) model to confirm the prediction accuracy of CFD analysis of human coughing based on the experimental results of particle image velocimetry (PIV). The projection area of the mouth, which is the boundary condition of airflow generated by human coughing, was assumed as an ellipse shape, major axis length was 43.2 mm (1.7 in), and the ratio of the major and minor axis was 4. Because the air velocity corresponding to the boundary condition of the mouth in the CFD model cannot be derived directly from the PIV results, the time-series airflow distribution was analyzed by introducing a correction factor, and the boundary condition with the smallest error with the experimental result was inversely derived. As a result, the airflow generated by coughing with CFD analysis could be reproduced with an RMSE of 0.38–0.42 m/s (1.25–1.38 ft/s) compared to the ensemble average obtained in the experiment. This study provides detailed modeling techniques and boundary conditions of numerical simulation for analyzing the airflow characteristics generated by human coughing. In addition, it is expected that the risk and route of infection caused by human coughing can be predicted through CFD analysis by additionally measuring the size distribution of droplets and droplet nuclei and introducing Lagrangian analysis.