Liquid-droplet coalescence and liquid-lens mergers are relevant in pharmaceuticals, oil recovery, food industries, and climate-system science. In order to obtain flow fields from experimentally measured concentration fields in both viscous and inertial regimes, this paper offers a framework of convolutional neural network machine learning models trained using data from direct numerical simulations.
- Vasanth Kumar Babu
- Nadia Bihari Padhan
- Rahul Pandit
