Improving the predictability of interfacial phenomena

PN 6 A-2

Project description

The comparison of experimental data and results from numerical simulations - and thus the complete description of a physical process - is often difficult, since usually only two-dimensional information can be obtained from the experiments. Therefore, the proposed project aims to develop innovative modelling approaches that will provide a comprehensive picture of the physical phenomena under investigation. These are based on the interplay of direct numerical simulations, imaging experimental investigations and the the three-dimensional reconstruction of images based on artificial intelligence. A drop impacting on a smooth or structured surface with a possible disintegration can be understood as an exemplary case, where this new approach is applied. For this case, physical phenomena will be investigated and modelled. DNS not only provides a deep insight into the underlying physics and is the basis for the modelling of the process, it also allows the creation of huge data sets to train AI.

Project information

Project title Improving the predictability of interfacial phenomena - Description of complex drop-wall interactions in the interaction of experiments, direct numerical simulations and innovative modelling approaches based on artificial intelligence
Project leader Kathrin Schulte
Project partners Jochen Kriegseis (KIT)
Alexander Stroh (KIT)
Project duration March 2021 - February 2024
Project number PN 6 A-2

Publications PN 6 A-2

  1. 2022

    1. J. Potyka et al., “Towards DNS of Droplet-Jet Collisions of Immiscible Liquids with FS3D,” High Performance Computing in Science and Engineering ’22, Springer International Publishing, 2022. [Online]. Available:
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