Bubble clouds in viscoplastic fluids

TL;DR

This study investigates how bubbles in viscoplastic fluids can be trapped without motion, revealing that the critical yield number increases with bubble volume fraction and short-range interactions, with a new algebraic model proposed.

Contribution

It provides the first detailed numerical analysis of bubble clouds in viscoplastic fluids, establishing the relationship between yield number and bubble volume fraction and introducing a semi-empirical algebraic model.

Findings

Critical yield number increases linearly with volume fraction in dilute regimes.

Short-range bubble interactions significantly raise the critical yield number.

An algebraic expression approximates the critical yield number for volume fractions up to 0.31.

Abstract

Viscoplastic fluids can hold bubbles/particles stationary by balancing the buoyancy stress with the yield stress. In the present study, we investigate a suspension of bubbles in a yield-stress fluid. More precisely, we compute how much the gas fraction $\phi$ that could be held trapped in a yield-stress fluid without motion. The key parameter is the yield number which represents the ratio of the yield stress to the buoyancy stress. Here the goal is to shed light on how the bubbles feel their neighbours through the stress field and to compute the critical yield number for a bubble cloud beyond which the flow is suppressed. We perform 2D computations in a full periodic box with randomized positions of the monosized circular bubbles. A large number of configurations are investigated to obtain statistically converged results. We intuitively expect that for higher volume fractions the critical yield number is larger. Not only here do we establish that this is the case, but also we show that short range interactions of bubbles increase the critical yield number even more dramatically for bubble clouds. The results show that the critical yield number is a linear function of volume fraction in the dilute regime. An algebraic expression model is given to approximate the critical yield number (semi-empirically) based on the numerical experiment in the studied range of $0\le \phi \le 0.31$, together with lower and upper estimates.