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Data Flow Lab is an interdisciplinary research group that tackles real-world problems of micro-scale fluid/solid interactions by harnessing the power of data science. We develop computationally-efficient image-based techniques to investigate the world of flow in micro-structures from subsurface water and energy resources to the amazing world of living cells and tissues.
Basically, everywhere that fluid is passing through a lifeless or live mass, you can find a capillary network. It is an inherent and fundamental solution that nature invented to transport fluids within the solid bodies from the cardiovascular system, bones, and lungs to geological outcrops and subsurface water resources. Thus, there would be a great benefit in understanding how fluid is going through these networks and what are the fluid-solid interactions that happen at the micro-scale.

Porous material modeling

Micro-computed tomography can be used to study the porous material's internal structure. Pore network modeling is often used to simplify these complex geometries into lightweight proxy models that represent the same behavior as the real geometry. Such models can help in understanding the fluid-solid interactions in several intricate engineering fields from fuel cells and batteries to water purifiers and filters. In the above illustration, you can see an example of extracted pore network model done by our group.

Vessel segmentation and flow modeling

Realistic models of body vessels and capillaries can be constructed based on medical images. These models are extremely useful for diagnostic and prognostic purposes. Biomechanical simulation of processes that occur in living organs can open new horizons in making patient-specific models and treatments and reduce medical risks. In the above illustration, you can see the segmentation of blood vessels based on a retinal fluorescein angiography image done by our group.