Aerospace professor to study physics of infectious disease spread with NSF award

By Cassie Montgomery

Published: Feb 19, 2021 8:33:00 AM

The ability to predict the dispersal of respiratory aerosols is a critical component in understanding infectious disease spread. The ability to predict the dispersal of respiratory aerosols is a critical component in understanding infectious disease spread.

Being able to predict how droplets are dispersed during coughing, sneezing or speech is critical to understanding the spread of infectious diseases such as COVID-19. Assistant aerospace engineering professor Vrishank Raghav will lead a combined $464,846 National Science Foundation award, in collaboration with the University of Michigan, to explore this topic. In this project, the collaborative team will take existing industry and academic tools a step further by considering the underlying turbulent flow physics at play. 

“Droplet-laden flows are ubiquitous both in engineering applications and in nature. For example, fuel injection in engines, paint sprays, air pollutants, platelets in blood, respiratory aerosols, to name a few,” Raghav said. “Our research group started conducting experiments to quantify speech generated aerosols at the onset of the pandemic, and this NSF grant will help us continue this work. For this study, we will be using a combination of human subjects and an ex-vivo cough simulator at Auburn University to achieve our goals.” 

In pursuit of these goals, Raghav, in collaboration with researchers at the University of Michigan, will combine 3D time-resolved velocimetry with an extensively validated fluid-particle simulation method, to uncover new flow physics relating the influence of flow interactions on the entrainment and dispersion of droplets. This combined approach will make advances toward the development of improved reduced-order models that could be easily embraced through direct implementation into existing tools. 

“Such improved quantification of flow physics and the development of reduced-order models will enable better prediction of droplet dispersion, a key step toward understanding the spread of viral infections,” he said. “The methods developed will be used to study the interaction of droplet-laden expiratory jets with flow barriers, for example face masks and face shields, and evaluate their efficacy to mitigate the dispersion of expiratory flows and contain outbreaks.” 

The researchers also plan to incorporate their findings into ongoing efforts with the Office of Student Services to adopt virtual reality-based imaging to enable immersive 3D representations of droplet-laden expiratory flow as an educational tool for use in outreach events and workshops.

Media Contact: Cassie Montgomery,, 334.844.3668

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