A predictive model for bubble–particle collisions in turbulence

The modelling of bubble–particle collisions is crucial to improving the efficiency of industrial processes such as froth flotation. Although such systems usually have turbulent flows and the bubbles are typically much larger than the particles, there currently exist no predictive models for this case which consistently include finite-size effects in the interaction with the bubbles as well as inertial effects for the particles simultaneously. As a first step, Jiang and Krug [2025] proposed a frozen turbulence approach which captures the collision rate between finite-size bubbles and inertial particles in homogeneous isotropic turbulence using the bubble slip velocity probability density function measured from simulations as an input. In this study, we further develop this approach into a model where the bubble–particle collision rate can be predicted a priori based on the bubble, particle, and turbulence properties. By comparing the predicted collision rate with simulations of bubbles with Stokes numbers of 2.8 and 6.3, and particles with Stokes numbers ranging from 0.01 to 2 in turbulence with a Taylor Reynolds number of 64, good agreement is found between model and simulations for Froude number Fr ≤ 0.25. Beyond this range of bubble Stokes number, we propose a criterion for using our model and discuss the model’s validity. Evaluating our model at typical flotation parameters indicates that particle inertia and settling effects are usually important. Generally, smaller bubbles, larger particles, and stronger turbulence increase the overall collision rate.