International Journal of Multiphase Flow最新文献

The paper examines two numerical approaches to the simulation of electrical deformation and coalescence processes in water-in-oil emulsions: the phase-field method and the arbitrary Lagrangian–Eulerian approach. The former employs a diffuse interface, while the latter utilizes a sharp interface. The study analyzes the correctness of the computer simulation results and identifies less obvious limits of the applicability of these numerical techniques. The paper is based on a step-by-step comparison of data from two independent numerical models and quantitative verification using original experimental data, including data on unsteady-state droplet deformation and the threshold between coalescence and non-coalescence. The main findings are as follows. Both methods, the modified phase-field approach and the arbitrary Lagrangian–Eulerian one, are fundamentally capable of providing physically and quantitatively correct results for modeling electrohydrodynamic processes in two-phase immiscible liquids. On the one hand, the phase-field method demands thorough tuning and has limited applicability for simulating long-term processes. On the other hand, the arbitrary Lagrangian–Eulerian approach offers greater precision and requires fewer computational resources compared to the phase-field method, although it demands a manual adjustment of geometry when the system's topology changes. It is noteworthy that the phase-field method, without careful tuning, fails to yield quantitatively accurate results; errors, such as discrepancies in the time convergence of droplets under the influence of an electric field, can reach magnitudes of tens of percentages.

Ionic liquid compressors are the ideal solution for hydrogen refueling stations, and multi-stage compression is an inevitable choice for achieving high-pressure refueling, such as 90 MPa level. However, the initial filling amount of the ionic liquid in the compression chamber is lacking basis as the characteristics of gas-liquid two-phase flow during the reciprocating movement of the liquid piston are not understood. This study numerically investigates the variation characteristics of the gas-liquid interface in the compression chambers under different structural and operating parameters of a five-stage ionic liquid compressor. Based on the fluctuation feature of the phase interface, the minimum liquid piston heights in each stage that ensure effective sealing for the compression chamber with different stroke-to-diameter ratios (r) are determined. Finally, the mathematical relationship for calculating the minimum ionic liquid filling amount related to structural parameter r and suction pressure is established, which provides guidance for the design of the ionic liquid compressor.

In this paper we report on direct numerical simulations of turbulent convection in a cuboidal pool that contains liquid water in the lower part and air in the upper one. The bottom wall is uniformly heated and natural convection is established in both phases, accompanied by water evaporation across the free surface of the water. The descent of the free surface due to evaporation is computed via a newly developed tracking algorithm based on the ghost-fluid method. We present results for three different cases which correspond to different pool heights. In all of them, the natural convection in the water lies in the soft-turbulence regime. Whereas in the gas, it lies in the laminar, transitional and soft-turbulence regimes, respectively. Our analysis focuses on the characteristics of the convective patterns in the two phases and the statistics of the various flow quantities of interest. According to our simulations, the flow in the water is organized in a single-roll Large-Scale Circulation (LSC). In the gas, it is organized in single or dual-roll LSCs, depending on the aspect ratio of the pool. Interestingly, the impingement points of the LSCs of the two phases at the free surface remain very close to one another, which is attributed to the continuity of the shear stresses across the free surface. Further, after the initial transient period, both the free-surface temperature and the evaporative mass flux are stabilized and remain almost constant, but they exhibit small-scale fluctuations in time due to turbulence. Also, the transport of water vapor in air has similar properties as the heat transport, and the ratio between the Sherwood and Nusselt numbers is very close to the Lewis number for air.

The influence of cavitation on the mean characteristics and unsteady behavior of turbulent separated flows was comprehensively investigated in this study over a microscale backward-facing configuration at the Reynolds number ($R{e}_D$) of 7440. The computational approach took both compressibility and finite mass transfer (Thermodynamic non-equilibrium) into account, to accurately capture the effects of shock waves, as well as to capture baroclinic phenomena on vortex dynamics within the turbulent separated flow. The compressibility effects were handled by using appropriate equation of states for each phase and for the mixture. Phase-change was considered through a transport equation for the vapor volume fraction, allowing for finite mass transfer contributions. Additionally, a wall adaptive large eddy simulation (LES) approach was utilized for simulating turbulent structures and their effects. The findings reveal that vapor development diminishes the mean growth rate of the shear layer and delays its reattachment to a longer distance from the step. Moreover, analysis of Reynolds normal and shear stresses, as well as the root mean square (RMS) of pressure fluctuations, demonstrates that the formation and collapse of vapor packets significantly influence turbulence decay and production in the second half of the shear layer and reattachment. It was also observed that both mean pressure and pressure fluctuations increased in vicinity of the reattachment region when cavitation was present, which was attributed to the condensation and collapse events. Spectral analysis further indicates the emergence of two dominant low frequency modes, linked to the displacement of the reattachment point. In the presence of cavitation, the frequencies associated with dominant Power Spectral Densities (PSDs) were smaller than those in the absence of cavitation. Additionally, each of these low frequencies corresponded to a specific vapor transport mechanism within the Turbulent Separation Bubble (TSB). Furthermore, it is shown that cavitation leads to a significantly higher spectral energy of high frequency fluctuations within the reattachment region in comparison to the condition where cavitation is absent. This can be attributed to the frequent collapse of bubbles in this region. At the end, we employed Spectral Proper Orthogonal Decomposition (SPOD) for modal analysis. This method offers valuable insights into the coherent structures and associated frequencies that arise in both the presence and absence of cavitation, which provides a deeper understanding of the effect of cavitation on the coherent structures and their dynamics.

There is a substantial amount of information embedded in images of two-phase flow captured through high-speed video (HSV) or high-resolution photography. However, accurate image segmentation is necessary to unlock a meaningful analysis of the data. In this study, we discuss how to estimate the flow void fraction in chevron-type corrugated channels typical of compact plate heat exchangers (CPHE) from back-lit front-view HSV images, using machine learning (ML) algorithms and data processing techniques. A U-Net neural network was employed for image segmentation, demonstrating robust performance with evaluation metrics consistently exceeding 0.9. The binary masks (indicating gas or liquid phases) derived from segmentation were processed in MATLAB® to estimate void fraction through a 3D reconstruction algorithm of the gas cluster’s volume. In contrast to conventional void fraction estimates based on the area ratio of binary masks, this algorithm models the curvature of the liquid-vapor interface through the corrugated channel. When compared to other methods, our algorithm predicts very similar void fraction contour maps. However, the average discrepancy between our algorithm and the area-ratio approach can be as high as 80%, underscoring the importance of the processing method in analyzing the data and developing correlations. Finally, a drift flux model was introduced to predict the void fraction distribution using a two-part equation accommodating the dependency of the distribution coefficient $C_0$ on the liquid flow rate for a corrugation Froude number $F{r}_{\sim }$ larger than 1. The proposed model can predict the void fraction dataset with a mean average percentage error of 8.17%. In summary, U-Net’s pixel-level accuracy facilitates deep and precise post-processing of HSV images, enabling meaningful void fraction measurements. Thanks to its generality and minimal training effort requirements, the discussed methodology can be applied to estimate void fractions in various two-phase flow experiments and operating conditions.

Previous studies on polydispersed bubbly flow in continuous casting (CC) mold were mainly attentive to the modeling of shear-induced turbulence, interfacial force, and bubble swarm effects. The current study reveals the coalescence and breakup mechanisms of bubbles in CC mold. Then, a calibration factor of coalescence kernel is proposed based on local gas holdup to harmonize the imbalance between coalescence and breakup rates. The effect of bubble coalescence and breakup models on the Sauter mean diameter, gas holdup, and liquid velocity were studied and against with the experimental data. The results show that the Turbulent and Liao models underestimate the bubbles coalescence rate and the Luo coalescence model overestimates the bubbles coalescence rate. Meanwhile, turbulence shear and surface instability overestimate the bubble breakup frequency, and turbulent impact is the most important mechanism used to describe bubble breakup phenomenon in the CC mold. Furthermore, the turbulent fluctuation, buoyancy driven, and wake entrainment should be considered to define the bubbles collision frequency, while the viscous shear and eddy capture mechanisms could be neglected. The Luo-Prince model could accurately predict the bubble size distribution and the fan-shaped distribution of bubble clusters, which comprehensively considers three collision mechanisms. Finally, the combination form of calibration factors could effectively describe the influence of local gas holdup on bubble collision frequency. The proposed calibration factor can predict bubble size distribution more accurately in the CC mold. The relative error of mean bubble diameter prediction is reduced from 63.53 % to 17.86 %.

Ducted fuel injection (DFI) has the potential to reduce soot emissions with respect to free injection. To explore the spray performance of DFI under different ambient pressures as well as to keep up with the trend of high intensification in diesel engines, a LES numerical model was adopted to investigate and analyze the spray behavior of DFI in the perspectives of spray development and gas entrainment under the ambient gas pressure ranges from 3 MPa to 12 MPa. The numerical results were validated by the visualization experiment. Free spray was targeted for comparison with DFI spray. The investigation results indicated that the difference between DFI spray and free spray is attributed to the spray-duct interaction. The ambient gas between duct wall and spray acts as a pivot to achieve the spray-duct interaction. With ambient pressure increasing, more ambient gas plays the pivotal role. The axial and overall development of DFI spray is faster than those of free spray, and the advantage is more obvious with increasing ambient pressure. The pressure difference between the inside and outside of duct causes a regular gas entrainment at the duct inlet. The pressure drop ratio and the gas entrainment rate both decrease as ambient pressure increases.

A comprehensive experimental investigation is conducted to analyze the effects of momentum ratio and impingement angle on impinging spray characteristics of triplet and pentad injectors by using Phase Doppler Anemometry (PDA) and a mechanical patternator. Results from the triplet and pentad injectors show that an increase in the momentum ratio causes a decrease in the mass flux, resulting in a more uniform spray distribution. It is observed that this leads to better atomization in terms of the normalized droplet count with triplet injectors. In addition, when compared to the 45° and 60° impingement angles at the same momentum ratio, the 90° impingement angle gives a higher number of droplets spread over a larger region for triplet injectors. In contrast, the normalized droplet count decreases with an increase in the impingement angle and momentum ratio in the case of pentad injectors. It is observed that for the impingement angle of 60°, triplet injectors are superior to pentad injectors in terms of atomization. The triplet injector with an impingement angle of 90° offers improved atomization at higher momentum ratios compared to all configurations studied. For both injector types, the 45° impingement angle produces a poor spray distribution. The spray angle is observed to be a strong function of both the impingement angle and momentum ratio for triplet injectors, while it is relatively less affected by these two parameters for pentad injectors.

In this contribution, we derive a gas–liquid two-scale multi-fluid model with capillarity effects to enable a novel interface regularization approach for multi-fluid models. As this unified modelling is capable of switching from the interface representation of a separated to a disperse regime it lays a new way of modelling regime transitions as it occurs in atomization processes. Above a preset length threshold at large scale, a multi-fluid diffuse interface model resolves the dynamics of the interface while, at small-scale, a set of geometric variables is used to characterize the interface geometry. These variables result from a reduced-order modelling of the small-scale kinetic equation that describes a collection of liquid inclusions. The flow model can be viewed as a two-phase two-scale mixture, and the equations of motion are obtained thanks to the Hamilton’s Stationary Action Principle, which requires to specify the kinetic and potential energies at play. We particularly focus on modelling the effects of capillarity on the mixture’s energy by including dependencies on additional variables accounting for the interface’s geometry at both scales. The regularization of the large-scale interface is then introduced as a local and dissipative process. The local curvature is limited via a relaxation towards a modified Laplace equilibrium such that an inter-scale mass transfer is triggered when the mean curvature is too high. We propose an original numerical method and assess the properties and potential of the modelling strategy on the relevant test-case of a two-dimensional liquid column in a compressible gas flow.

In this article, we present a deep learning-based surrogate model for spatio-temporal prediction of cavitating fluid flow. Specifically, we introduce a finite element-inspired rotation equivariant hypergraph neural network for inferring and predicting dynamical behaviors of cavitating flow. We generate ground-truth spatial–temporal data by simulating a full-order variational system based on homogeneous mixture-based cavitation theory. We consider the flow past a NACA0012 hydrofoil to examine the predictive ability of the proposed graph neural network for cavitation dynamics. Results demonstrate that the network achieves stabilized and accurate temporal predictions of the system states, successfully forecasting the evolution patterns of individual cavitation events. Additionally, comparisons of predicted fluid loading coefficients are in good agreements with the ground-truth values. We also discuss some challenges encountered in the long-term prediction of flow patterns across multiple cavitation events. The proposed framework has implications for design optimization, active control and development of a physics-based digital twin of a cavitating marine propeller.