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Multiscale Modeling of Fluid Materials


Magistrale, Stand 19

LeitungProf. Julija Zavadlav


Most scientific phenomena across various fields, ranging from life sciences to engineering, are multiscale in nature since the associated processes are determined by the interplay of disparate spatial and temporal scales. In our group, we are focusing on tackling such problems with multiscale modeling and simulations, where we merge micro and meso/macroscopic models or methods. These state-of-the-art approaches are essential, also from the point of view of computational efficiency. The meso/macroscopic fluid dynamics description may not describe the system with sufficient detail, while the nanoscale description is computationally too demanding. We use many machine learning techniques to advance the field even further. The research interests of our group, therefore, lie at the crossroads between multiscale simulations, machine learning, engineering, and high-performance computing.


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