Applied Mathematics Colloquium – Tian Ma, Institute of Fluid Dynamics (Helmholtz-Zentrum Dresden–Rossendorf)

Title-Bubble clusters and particle-pair dispersion in bubble-laden flows

Abstract-Bubble clusters We use experiments to study the evolution of bubble clusters in a swarm of freely rising, deformable bubbles. A new machine learning-aided algorithm allows us to identify and track bubbles in clusters and measure the cluster lifetimes. The results indicate that contamination in the carrier liquid can enhance the formation of bubble clusters and prolong the cluster lifetimes. The mean bubble rise velocities conditioned on the bubble cluster size are also explored, and we find a positive correlation between the cluster size and the rise speed of the bubbles in the cluster, with clustered bubbles rising up to 20% faster than unclustered bubbles. Particle-pair dispersion Bubble-induced turbulence (BIT) plays an important role in mixing, transport and collision of small particles in many natural and industrial applications. A crucial component of the Lagrangian description of BIT is the relative pair dispersion, based on the relative separation of pairs of fluid particles. In the present work, we report the first experimental study of tracer particle-pair dispersion in BIT for varying initial separations. To this end, 3D Lagrangian Particle Tracking measurements are carried out in an octagonal bubble column, where the flow is generated by a homogeneously distributed bubble swarm rising in water. Our results show that the relative dispersion follows the classical ballistic regime at short times and is almost independent of the initial separation 𝑟0, when 𝑟0 = 𝑂(10𝑑𝑏), with 𝑑𝑏 the bubble diameter. In order to fully characterize the particle-pair dispersion in BIT, we also measure the anisotropy of the dispersion using the barycentric map and show that it increases with increasing initial separation.