International Journal of Multiphase Flow最新文献

Bubble-induced convection governs the flow pattern inside parallel plate electrolyzers, independent of the superficial electrolyte velocity. At the electrode surface, gas bubbles nucleate, grow and detach, increasing the gas volume fraction and accelerating the electrolyte in the proximity of the electrode. This acceleration due to buoyancy-induced bubble velocity enhances the mixing and mass transport, impacting the local concentration and, hence, the electrochemical reaction. To study the velocity and size of electrogenerated gas bubbles, we present a particle tracking velocimetry method that enables the velocity measurement directly inside the bubble curtain of a membrane-separated, parallel plate electrolyzer. By decoupling the effect of the bubble size on the bubble velocity, we study the impact of different current densities and superficial velocities of the electrolytes on the vertical bubble velocity. Our results reveal the strong dependence of the bubble velocity on the total net volume of produced gas and the thereby linked acceleration of the electrolyte near the electrode. Under no net electrolyte flow conditions, the determined vertical bubble velocities inside the bubble curtain double to triple values of single bubble experiments and predictions by commonly used drag correlations. By applying forced convection, the measured vertical velocity of equally sized bubbles decreases and shifts towards the superficial electrolyte velocity. Additionally, the horizontal bubble velocities increase at higher electrolyte velocities, indicating a broadening of the bubble curtain, as also proposed by numerical studies. The presented findings improve the understanding of gas-liquid flows in electrolyzers and, thus, the efficiency of gas-evolving parallel-plate electrolyzers.

The spreading and shrinking processes of the liquid film caused by the impingement of water drop on an inclined cylindrical surface are two important aspects reflecting the dynamic behavior. In this paper, the parametric effects of the liquid film spreading and shrinking processes were investigated by using an experimental approach. The time-dependent evolutions of the dimensionless spreading lengths (axial and circumferential) under various impingement situations were indirectly derived by image post-processing. It is discovered that, when the cylinder is tilted, the liquid film will go through one more stage in the spreading process compared with when it is horizontal, i.e., the sliding stage, which facilitates the spreading of water drop into a larger liquid film. The time at which the spreading lengths in the axial and circumferential directions reach their maximum is not consistent and determined by the inclination angles. There is a critical angle of 35°, which changes the relative magnitude between the maximum axial and circumferential spreading factors. Due to the breakage of the liquid film edge during shrinking process, satellite drops are more likely to form when the cylinder is tilted than when it is horizontal. The Weber number and inclination angle exert substantial influence on both the spreading and shrinking processes of the liquid film. However, the impact of the cylindrical surface temperature appears to be comparatively insubstantial. Finally, the correlations of the maximum and stable spreading factors were fitted. Among them, the mean relative deviations of the maximum circumferential and axial spreading factors are 12.2 % and 7.4 %, respectively, compared with the simulated and experimental data of single water drop impinging on horizontal cylindrical surfaces from other studies.

An accurate modeling of the bubble condensation phenomena in sub-cooled water is developed in this work, using a two-fluid model with one disperse phase and one Interfacial Area Transport Equation (IATE). For this, the aspects of some models are investigated, such as the choice of population balance models, Nusselt closure model and bubble collapse model in IATE. The standard method of moments is formulated using two different bubble size distribution functions among all, namely Dirac and quadratic laws. Therefore, different models for mass and energy interfacial transfers, interfacial forces and source terms of the IATE are developed using both functions. While limited differences are noticeable for the mass and energy transfers obtained by both functions, the results are largely improved using quadratic function for the drag force term and for the IATE source terms. Moreover, the simulations results show that the widely used Ranz-Marshall correlation clearly underestimates the condensation rate. However, this work shows that Chen–Mayinger correlation is relevant to simulate this type of flow, regardless the distribution function. Afterwards, a model is introduced to take into account the effect of bubble collapse by condensation in the IATE. The numerical results obtained using the quadratic function, the collapse model in the IATE and the Chen–Mayinger correlation are comparable to those obtained by the inhomogeneous MUltiple Size Group (iMUSIG) approach, while being less time-consuming.

Understanding the behaviors of suspension drops (particle swarms) as they settle in a viscous fluid holds significant importance across various applications. Due to hydrodynamic interactions (HIs), suspension drops would undergo a series of intricate behaviors, including shape deformation, disintegration, and coalescence. This work presents the hydrodynamic interaction graph neural network (HIGNN), developed in our prior work (Ma et al., 2022), as an efficient and accurate modeling framework for simulating the dynamics of suspension drops and investigating the various behaviors they exhibit. The HIGNN effectively incorporates the many-body nature of HIs, a feature lacking in most previous simulations that employ the Stokeslet assumption. In the meanwhile, the HIGNN achieves superior computational efficiency compared to traditional, high-fidelity numerical tools such as Stokesian dynamics and PDE solvers. Moreover, the HIGNN, once trained, is applicable to predicting suspension drops across a range of particle concentrations and under diverse forces (such as gravity and Coulombic interactions). Training the HIGNN only requires the data containing a small number of particles, leading to low training cost. Our results demonstrate that the HIGNN can effectively reproduce the various behaviors of suspension drops that were previously reported in literature. More specifically, a single, initially spherical drop slowly evolves into a torus-shaped drop, as particles escape from its rear and form a tail along the sedimenting direction. Subsequently, the torus breaks into secondary droplets, each undergoing a similar transition (deformation into a torus followed by disintegration), thereby leading to a repeating cascade. Further, we quantitatively analyze the correlation between the drop’s sedimentation velocity and volume fraction. We also propose new scaling laws for evaluating both the leakage rate of particles and the expansion rate of the horizontal radius of a suspension drop. For single suspension drops, we also systematically investigate how their dynamics is affected by their initial shapes and the formed tori’s aspect ratios, as well as with or without Coulombic interactions between particles. For a pair of suspension drops, we study the process of coalescence of two vertically aligned particles and examine the effect of introducing a horizontal offset on the subsequent breakup of the coalesced drop. All simulations were executed on a single GPU, with the computation of velocities for several thousand particles requiring less than five seconds per time step. This computational efficiency enables fast and resource-saving simulations of large suspension drops over extended time scales.

A common way to transport solids in large quantities is by using a carrier fluid to transport the solids as a concentrated solid/liquid mixture or slurry through a pipeline. Typical examples are found in dredging, mining and drilling applications. Dependent on the slurry properties and flow conditions, horizontal slurry pipe flow is either in the fixed-bed, sliding-bed or fully-suspended regime. In terms of non-dimensional numbers, the flow is fully characterized by the bulk liquid Reynolds number ($Re$), the Galileo number ($Ga$, a measure for the tendency of particles to settle under gravity), the solid bulk concentration (${\varphi }_b$), the particle/fluid density ratio (${\rho }_p/{\rho }_f$), the particle/pipe diameter ratio ($D_p/D_{pipe}$), and parameters related to direct particle interactions such as the Coulomb coefficient of sliding friction (${\mu }_c$). To further our fundamental understanding of the flow dynamics, we performed experiments and interface-resolved Direct Numerical Simulations (DNS) of slurry flow in a horizontal pipe. The experiments were performed in a transparent flow loop with $D_{pipe}=4$ cm. We measured the pressure drop along the pipeline, the spatial solid concentration distribution in the cross-flow plane through Electrical Resistance Tomography (ERT), and used a high-speed camera for flow visualization. The slurry consisted of polystyrene beads in water with $D_p=2\mathrm{mm}$, ${\rho }_p/{\rho }_f=1.02$, $Ga$ between 40–45 and ${\varphi }_b$ between 0.26–0.33. The different flow regimes were studied by varying the flow rate, with $Re$ varying from 3272 till 13830. The simulations were performed for the same flow parameters as in the experiments. Taking the experimental uncertainty into account, the resu