Abstract: Fluid mixing is a common technique used in combustion, emulsification, dispersion, agglomeration, and blending by numerous commercial and industrial sectors, including petrochemical, pharmaceutical, and agro-based businesses. In this talk, I will present results from modeling and data-driven approaches of binary fluid dynamics in different settings. In nature, fluid mixing may occur when pollutants are released into water, as in a large-scale oil spill, when oil and water mix. Recently, high resolution satellite images are available from Synthetic Aperture Radar (SAR) imagery of oceanic oil spills. We show preliminary results from a large number of test simulations using the open-source NOAA GNOME oil spill trajectory model. We validate our results obtained from the model against available satellite observations from the Synthetic Aperture Radar (SAR) database. Transitioning to the second part of the talk, I will present some results on the dynamics of a turbulent binary fluid system, in particular, a droplet moving in a turbulent fluid. Since extensive simulations are computationally expensive, I will show how we can leverage recent advances in interpretable, data-driven modeling techniques such as the Dynamic Mode Decomposition and the Sparse Identification of Nonlinear Dynamics to study the same binary fluid system, but at a much lower computational cost. These results demonstrate how we can successfully use data-driven strategies to reduce computational cost of large-scale models.
About the speaker: Dr. Nairita Pal did her bachelors in physics from Presidency College, Kolkata (2006 to 2009). After completing her bachelors she did her Masters in Physics from Indian Institute of Technology, Delhi (2009 to 2011). Dr. Nairita moved on to do her PhD in Physics from the Indian Institute of Science, Bangalore (2011 to 2017). Dr. Nairita has held prestigious positions such as a staff Scientist in the Los Alamos National Laboratory, USA (2017 to 2022) and an Assistant Professor at the Indian Institute of Technology, Kharagpur (2022 to present).