Research

The wind blows where it wills, and you hear the sound of it, but you do not know where it comes from and where it goes; 

                                                                -- John 3:8 a

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Two-dimensional Turbulence:

The majority of fluid flows in nature and engineering applications are turbulent. Turbulent flows are distinct because they display a characteristic cascade of energy. We use a thin-layer electromagnetic flow device to study two-dimensional turbulence. 
With the help of filter space techniques (FST) and a geometric perception of the turbulence cascade, we defined the efficiency of turbulence cascades. Moreover, my work revealed the missing piece in the well-known ''thinning mechanism".  
Currently, we are taking initiative steps of utilizing spatio-temporal data mining techniques to understand the Lagrangian nature of turbulent flows. 


Transport of non-spherical swimmers in turbulent flows:

The majority of fluid flows in nature and engineering applications are turbulent. Turbulent flows are distinct because they display a characteristic cascade of energy. We use a thin-layer electromagnetic flow device to study two-dimensional turbulence. 
With the help of filter space techniques (FST) and a geometric description of the turbulence cascade, we defined the efficiency of turbulence cascades. Moreover, my work revealed the missing piece in the well-known ''thinning mechanism".  
Currently, we are taking initiative steps of utilizing spatio-temporal data mining techniques to understand the Lagrangian nature of turbulent flows. 
*This work is supported by NSF.

 

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Biologically generated ocean mixing

Million of small organisms, paddling fluid, form dense aggregation. Can swimming organisms actually achieve significant mixing? We are using experimental methods to study this question. 

To tackle this many-body and multi-scale fluid-structure interaction problem, we are developing a novel particle tracking technique that can access length scales that is one order of magnitude larger than traditional methods. In addition, we will use a recently developed mathematical tool for understanding spectral energy transfer in such interaction. 

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Measuring and Simulating Social-distanced Crowds

Modeling a social-distanced crowd is of great importance because social distancing is one of the promising ways of reducing disease transmission during pandemic, post-pandemic, and flu season. Within a social-distanced crowd, individuals move and maneuver with an additional deliberate intention of keeping a minimum safety distance from their neighbors, which can lead to fundamentally unique behaviors. Moreover, the extra "buffer" space around the individuals imposes significant constrain on transportation mobility.

We are facing a situation where we do not have means that would help us to assess, estimate, and model operations of walking crowds in the new reality of corona-impacted conditions. Our group is using both agent-based modeling and advanced computer vision techniques to tackle this issue. 


*This work is supported by U.S. Army.