Probing the local response of a two-dimensional liquid foam

Abstract

Aqueous foams are viscoelastic yield stress fluids. Due to their complex rheology, foam flow around an obstacle embedded in a 2D Hele-Shaw cell has been widely studied. Typically, in such geometry in the moving flow reference frame the flow field of viscoelastic fluids exhibit a quadrupolar structure characterized by a negative wake. Here, we introduce a measuring geometry, new in this context, whereby instead of flowing the foam around the obstacle, we move the obstacle as an intruder inside the foam. The proposed setup makes it possible to independently control the driving velocity and the liquid foam properties, such as the gas fraction and polydispersity. We show that the liquid foam velocity field around the intruder is similar to the one observed in viscoelastic fluids, in particular the emergence of a negative wake, e.g. a velocity overshoot downstream side of the obstacle. However, surprisingly, the intensity of this velocity overshoot decreases with the number of intruder passes, probably related to the evolution of the local disordered structure of the liquid foam.

Machine learning and predicting the time-dependent dynamics of local yielding in dry foams

“…T2 events require either film breakup or gas exchange to occur, making them less frequent compared to T1s in systems under continuous deformation. A quasi-2D setting or simplifying geometry, is often used to study the flow of foams and T1s therein [10][11][12][13][14]. The T1 events can be either reversible or nonreversible depending on the geometric configuration and the stress direction [15,16].…”

Effect of Additives on the Foam Behavior of Aviation Coolants: Tendency, Stability, and Defoaming

“…The major difference is that the foam volume and defoaming time of the former are slightly higher than that of the latter, indicating that the sodium molybdate inorganic salt has little effect on the foam tendency of GA solution. However, the preservative n -caprylic acid, as an anionic surfactant, contributes to increased formation of micelles in the base solution, 22 resulting in the formation of lots of stable bubbles. As shown in Figure 2 c, the volume of generated foam reaches up to 350 mL after ventilating for 5 min, and the foam volume is not affected by the ventilation time.…”

Machine learning and predicting the time dependent dynamics of local yielding in dry foams

“…T2 events require either film breakup or gas exchange to occur, making them less frequent compared to T1s in systems under continuous deformation. A quasi-2D setting or simplifying geometry, is often used to study the flow of foams and T1s therein [10][11][12][13][14]. The T1 events can be either reversible or non-reversible depending on the geometric configuration and the stress direction [15,16].…”