Modal analysis and interface tracking of multiphase flows using Dynamic Mode Decomposition

Non-invasive visualization techniques for multiphase flows are critical to understanding primary atomization and sprays. We use back-lit imaging to identify the liquid-gas interface of two-phase flows at high temporal and spatial resolutions and employ Dynamic Mode Decomposition (DMD) to study the shape and frequency of instabilities of a liquid jet surrounded by a coaxial annular airblast atomizer. However, DMD is not suitable for interface tracking, so we develop a data-driven two-step approach using the optical sensor data. The method uses DMD on the optical flow field estimated from image snapshot pairs. We demonstrate our method to a representative toy problem of an oscillating drop and on the primary atomization of a numerical planar liquid jet. Finally, we apply our method to the experimental liquid jet from the coaxial airblast atomizer using back-lit imaging. Our method is able to accurately reconstruct and predict the flow and preserves the sharpness of the fluid interface.

Automated summary

Non-invasive visualization techniques are essential for understanding primary atomization and sprays in multiphase flows. The researchers in this study used back-lit imaging and Dynamic Mode Decomposition (DMD) to identify the liquid-gas interface and analyze the instabilities of a liquid jet surrounded by an airblast atomizer. However, DMD was not suitable for interface tracking, so they proposed a data-driven two-step approach using optical sensor data. The method successfully reconstructed and predicted the flow while maintaining the sharpness of the fluid interface.