Lei Fang, PhD

706 Benedum Hall | 3700 O’Hara Street | Pittsburgh, PA 15261 P: 412-624-8618

lei.fang@pitt.edu Assistant Professor

Lei Fang is an Assistant Professor in Civil and Environmental Engineering at the University of Pittsburgh. His research focuses on turbulence dynamics and transport and mixing problems with particular emphasis on topics relevant to biology, environment, and health. Current interests include the transport of active non-spherical swimmers, biologically generated mixing, human crowd dynamics, and the development of new experimental methods. Prior to joining the faculty at the University of Pittsburgh, he received a PhD from Stanford University in the Civil and Environmental Engineering Department with a PhD minor in Computational and Mathematical Engineering.

The three main ongoing projects are:

Active Matters in Dynamic Flow Environment

Chaotic and turbulent fluid flow in natural and engineered systems is usually embedded with active matters, such as fish schools in the oceans and swarms of swimming/flying robots. Even though the dynamical transport barrier (the flow structures that partition the flow domain into disconnected regions) is an efficient way to understand and control the transport of inactive material, it is not the case for modeling and controlling active matters because the coupling between dynamical transport barriers and the active matter is more complicated than that of inactive matters. There are three major challenges. First, agents in the active matters have mobility, so they don’t follow the flow exactly. Second, agents will generate small scale flow, and they can couple back to the larger scale flow collectively. Third, the challenge also comes from the significant scale mismatching between the small scale agents and large scale transport barriers. Typically, agents are usually few orders of magnitudes smaller than the transport barriers. We developed a combination of quasi-two-dimensional laboratory flow equipment, particle tracking velocimetry system, and light guiding system for the active matters. With the unique combination of the experimental system, we are able to tackle the complicated interactions with a wide range of parameter space.

Macroscopic Behavior of Social Distancing

The recent outbreak of COVID-19 has spread globally. We can prevent its spread by applying social distancing, which requires extra “buffer” space around each person, which poses significant constraints on transportation mobility. From the perspective of civil and environmental engineers, we are facing a situation where we do not have means which would help us to assess, estimate, and model operations of pedestrians in the new reality of corona-impacted conditions. A novel computational social distancing crowd model has been developed to study the macroscopic behavior with social distancing. Currently, the research goal is to identify the possibility of small modifications of existing infrastructure to enhance the transportation efficiency of the infrastructure. The proposed method will help develop mobility practices that can help us remain active and open our social and professional lives in pandemic and post-pandemic times.

Turbulence Behind Virus Transmission

The exhaled air of infected humans is one of the prime sources of contagious viruses, resulting from respiratory events such as coughing, sneezing, breathing, and talking. Coughing and sneezing have been widely studied because of higher exhalation velocity and droplet concentration. Less emphasis has been put on talking. However, talking can potentially have a strong effect due to longer duration and more direct exposure. Moreover, researchers have focused on contagious droplets, but surprisingly little attention has been paid to the turbulent nature of the carrier flows given their importance. Hence, our research focuses on the turbulence characterization of the talking plume. The turbulent talking plume can play an essential role in virus transmission because turbulence characteristics can determine a wide range of parameters in contagious droplets, such as evaporation rate and travel distance. Virus transmission is more complicated in talking plumes than plumes from coughing or sneezing because of the wide range of turbulent plumes from different pronunciations. We are setting up a novel particle-tracking technology that can track droplet trajectories that are at least one order of magnitude longer than the traditional particle tracking techniques.