Related papers: Machine learning models for the secondary Bjerknes…
Gas bubbles in a sound field are submitted to a radiative force, known as the secondary Bjerknes force. We propose an original experimental setup that allows us to investigate in details this force between two bubbles, as a function of the…
Most of the current applications of acoustic cavitation use bubble clusters that exhibit multibubble dynamics. This necessitates a complete understanding of the mutual nonlinear coupling between individual bubbles. In this study, strong…
It is known that in a certain case, the secondary Bjerknes force, which is a radiation force acting between pulsating bubbles, changes, e.g., from attraction to repulsion as the bubbles approach each other. In this paper, a theoretical…
The primary Bjerknes force is responsible for the quick translational motion of radially oscillating bubbles in a sound field. The problem is classical in the case of small-amplitude oscillations, for which an analytical expression of the…
Exploiting the full potential of MBs for applications requires a good understanding of their complex dynamics. Improved understanding of MB oscillations can lead to further enhancement in optimizing their efficacy in many applications and…
The outcome of this paper was a shape of the interaction of two oscillating bubbles. This was done to express the secondary Bjerknes force using the Maxwell equations for a liquid. These subsequent equations were written for the quantities…
Numerically calculating the interaction forces between two free bubbles under the action of a background of random acoustic radiation, we highlight the contributions of radiative coefficient and absorption damping coefficient to the size of…
In this paper it was shown that, under certain restrictive conditions, Bjerknes secondary forces are attractive and proportionate to the product of the virtual masses of the two bubbles.
Acoustically driven air pockets trapped in artificial crevices on a sur- face can emit bubbles which organize in (interacting) bubble clusters. With increasing driving power Fernandez Rivas et al. [Angew. Chem. Int. Ed., 2010] observed…
In a companion paper, a reduced model for propagation of acoustic waves in a cloud of inertial cavitation bubbles was proposed. The wave attenuation was calculated directly from the energy dissipated by a single bubble, the latter being…
The analysis of the secondary Bjerknes force between two bubbles suggests that this force is analogous to the electrostatic forces. The same analogy is suggested by the existence of a scattering cross section of an acoustic wave on a…
Bubbles under vibration can behave in unusual ways, e.g., moving downward against the force of buoyancy. While the bubble downward motion due to the Bjerknes force is well known at acoustic frequencies close to the bubble resonant…
Micro-bubbles and bubbly flows are widely observed and applied in chemical engineering, medicine, involves deformation, rupture, and collision of bubbles, phase mixture, etc. We study bubble dynamics by setting up two numerical simulation…
Key features of the mechanical response of amorphous particulate materials, such as foams, emulsions, and granular media, to applied stress are determined by the frequency and size of particle rearrangements that occur as the system…
The non-linear dynamics of driven oscillations in the size of a spherical bubble are mapped to the dynamics of a Newtonian particle in a potential within the incompressible liquid regime. The compressible liquid regime, which is important…
Combining physics with machine learning models has advanced the performance of machine learning models in many different applications. In this paper, we evaluate adding a weak physics constraint, i.e., a physics-based empirical…
Bubble-particle collisions in turbulence are key to the froth flotation process that is widely employed industrially to separate hydrophobic from hydrophilic materials. In our previous study (Chan et al., J. Fluid Mech., vol. 959, 2023,…
One emerging application of machine learning methods is the inference of galaxy cluster masses. In this note, machine learning is used to directly combine five simulated multiwavelength measurements in order to find cluster masses. This is…
The present article addresses an early-stage attempt on replacing the analyticity-based sink strength terms in rate equations by surrogate models of machine learning representation. Here we emphasise, in the context of multiscale modelling,…
Stellar feedback created by radiation and winds from massive stars plays a significant role in both physical and chemical evolution of molecular clouds. This energy and momentum leaves an identifiable signature ("bubbles") that affect the…