Collaborative Research: Effective Face Masks to Mitigate COVID-19 Transmission: Insights from Multimodal Quantitative Analysis

在接下来的几年里，口罩很可能会成为一种关键的、广泛使用的“医疗器械”。因此，了解支持口罩抵御空气传播病原体的有效性的物理学比以往任何时候都更加重要。在新冠肺炎大流行中，口罩提供的保护已成为一个特别重要的问题，但口罩的流动物理很复杂，而且没有得到很好的研究。在呼气过程中，口罩内部压力的增加会将口罩向外推，导致周界渗漏增加。这种流固耦合问题是由口罩的结构设计和渗透性以及脸部的适合性决定的。咳嗽和打喷嚏等痉挛事件会产生高的瞬时排出速度，并显著降低口罩的外在保护作用。然而，在可以想象的未来，人们在日常生活中将戴上口罩，在呼吸和交谈等正常活动中进行外在保护可能同样重要。该项目的目标是(I)开发表征口罩性能所需的改进的计算和实验工具，(Ii)利用这些工具对各种条件下的口罩性能进行详细的表征，以及(Iii)及时生成可用于改进口罩设计和指导更有效的公共卫生政策的数据。该项目将开发一套创新、强大和准确的计算和实验工具，其基础是流动物理和力学，可用于定量分析口罩的防护性能。计算工具将流体流动与由多种面部几何定义的复杂几何中的弹性结构的运动相结合。实验工具将包括分别使用数字图像相关和粒子图像测速仪同时测量面罩运动和气雾云。可见光和X射线技术将被用来测量面具内外的尺寸。模拟和实验的综合结果预计将产生关于口罩保护性能的关键特征的见解，并为改进口罩设计和有效的公共卫生政策提供及时的指导。该项目将促进对理工科学生的多学科教育，并增加公众对有效面膜的流体动力学原理的了解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The years ahead will likely see face masks become a critical and widely used “medical appliance.” Understanding the physics that underpins the effectiveness of face masks as a defense against airborne pathogens is therefore more important than ever. The protection afforded by face masks has emerged as a particularly important issue in the COVID-19 pandemic, but the flow physics of face masks is complex and is not well-studied. The increased pressure inside the mask during expiration pushes the face mask outwards, resulting in increased perimeter leakage. This fluid-structure interaction problem is mediated by the structural design and the permeability of the mask, as well as the fit on the face. Spasmodic events such as coughing and sneezing generate high transient expulsion velocities and significantly diminish the outward protection of face masks. However, in a conceivable future where people will wear face masks while engaged in their daily routines, outward protection during normal activities such as breathing and talking, might be equally important. The objectives of this project are (i) to develop improved computational and experimental tools necessary to characterize the performance of face masks, (ii) to employ these tools to perform a detailed characterization of mask performance under a variety of conditions and (iii) to generate, in a timely manner, data that can be used for improved facemask design and to guide more effective public health policy.The project will develop a set of innovative, powerful and accurate computational and experimental tools, rooted in flow physics and mechanics that can be used for the quantitative analysis of the protective performance of face masks. Computational tools will couple fluid flows with the motion of elastic structures in complex geometries defined by a wide range of facial geometries. Experimental tools will include simultaneous measurements of mask motion and the aerosol cloud, using Digital Image Correlation and Particle Image Velocimetry, respectively. Visible and X-ray techniques will be used to take measurements outside and inside the mask. The combined results of the simulations and experiments are expected to yield critical insights regarding the features that contribute to the protective performance of masks, and to provide timely guidance for improved mask design and effective public health policies. The project will promote the multidisciplinary education of students in Science and Engineering, and increase public knowledge about the fluid dynamics principles of effective facemasks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.