International Journal of Multiphase Flow最新文献

Immiscible flow of oil phase and displacing phase with surfactant can cause emulsification during the oil development. However, it is still unclear how the viscosity of each phase influences the emulsification at the micro level. In this study, we investigated the flow regimes and emulsification of two immiscible fluids in a cross-junction device by using an oil-surfactant system and an oil-surfactant/polymer system. Based on the experimental data, we analyzed the flow regimes and draw flow regime maps of the two systems. Moreover, we established the new scaling laws that include the capillary number, the flow rate ratio, and the viscosity ratio of two phases to predict the droplet diameter or slug length. The findings indicated that there are four flow regimes in the oil-surfactant system, including threading, squeezing, dripping, and jetting regimes. Besides, a new type of flow regime, irregular dripping regime, appears in the oil-surfactant/polymer system. According to the regime maps, the area of dripping regime decreases with the increase of the viscosity of dispersed phase or continuous phase. For both systems, the regression equations with the viscosity ratio have better fitting effect than those without the viscosity ratio. Meanwhile, compared with the effect of viscosity ratio of two phases, the flow rate ratio of two phases has higher influence on droplet diameter and slug length. The experiments present detailed emulsification processes at pore scale and provide new insights for the prediction of emulsion droplets and slugs.

In this paper, we develop a deterministic drag model for stationary spherical particles in a Stokes flow using a cascade of data-driven approaches. The model accounts for the variation in drag experienced by each particle within fixed random arrangements. The developed model is a symbolic expression that offers explainability, ease of implementation, and computational efficiency. Firstly, we generate particle-resolved direct numerical simulation data of the flow past periodic random arrangements of stationary spherical particles with volume fractions between 0.05 and 0.4 using the method of regularized Stokeslets. Secondly, we train graph neural networks (GNs) on the generated data to learn the pairwise influence of neighbouring particles on a reference particle. The GNs are converted to symbolic expressions using genetic programming (GP), unveiling repeated subexpressions. Finally, these subexpressions constitute the foundation of the proposed algebraic model, further refined via non-linear regression. The proposed model can qualitatively mimic the pairwise influences as predicted by the GN and can capture the drag variations with accuracy from 74% and up to 84.7% when compared to the particle-resolved simulations. Due to the interpretability of the proposed model, we are able to explore how neighbour positions alter the drag of a particle in an assembly. The proposed model is a promising tool for studying the dynamics of particle assemblies in Stokes flow.

The objective of this paper is to investigate the multimodal partial shedding dynamics from a multiscale perspective of cloud cavitating flows under two distinct cavity shedding mechanisms, namely the re-entrant jet mechanism and the shock wave propagation mechanism. A two-way Eulerian–Lagrangian coupling algorithm is applied to capture the multiscale vapor topologies from microbubble to large-scale cavities. The large-scale cavity evolution is solved through large eddy simulations (LES) with the volume of fraction (VOF) method in Eulerian frame. The sub-grid microbubbles are tracked in Lagrangian frame based on the discrete bubble model (DBM) method. The predictions agree well with experimental observation of the periodical cavity evolution and microbubble dynamics under both the re-entrant jet mechanism and shock wave mechanism around a NACA66 hydrofoil. The numerical simulation provides detailed analysis of the cavitating turbulent flow on the microbubble behavior with emphasis on the spatial-temporal distribution characteristics of microbubbles. The results show that the number and mean size of microbubbles in the cavitation region increase gradually with the growth of attached sheet cavity, development of re-entrant jet and collapse of largescale cavity for both cavitation patterns. Meanwhile, microbubbles are mainly distributed on the largescale interfaces where have high value of vorticity and turbulent kinetic energy under the effect of re-entrant jet and vortex structures. And the probability density functions (PDFs) of microbubble exhibit gamma distributions with a dominant peak at approximately 50 μm for both shedding mechanisms. However, the shock wave formation and propagation process only occurs in the final stage of cavitating flow under shock wave mechanism causing the condensation of vapor and the decrease of the number and mean size of microbubbles. Moreover, the microbubbles are uniformly distributed along the streamwise and vertical directions behind shock wave front.

Cryogenic refrigerants represented by methane differ significantly in thermophysical properties from working fluids at ambient temperature. Thus, examining their small-scale heat transfer and flow characteristics is essential for designing compact condensers within the cryogenic field. The numerical simulation of methane condensation in minichannels is conducted, and the process of phase-change mass and energy transfer is investigated by programming. Detailed condensation flow field information is obtained, and surface tension and gravity influences are elucidated. Synergy analysis indicates that the synergy near the tube wall still needs to be improved. Heat transfer performance is proved to be dependent on the relative significance of turbulence intensity and condensate film thickness. The tube inclination exerts a more noticeable influence on the condensation heat transfer for large diameters, which is supported by the dominance of gravity in the condensation heat transfer mechanism at larger diameters. At higher vapor quality and mass flux, the heat transfer enhancement governed by surface tension is more significant. The condensate at the bottom is mainly formed by the accumulation of condensate sliding off the tube top driven by gravity as the diameter increases, reducing the heat transfer region. The mass flux augments the frictional pressure drop more noticeably at high vapor quality. The prediction performance of empirical correlations is evaluated, and all the selected correlations underestimate the frictional pressure drop of methane. Moreover, the figure of merit analysis demonstrates that the pressure drop produced by diameter reduction is more substantial than heat transfer enhancement, suggesting the requirement to assess the pressure drop loss in practical applications.

We show that a pipe transporting gas and liquid can be operated at conditions where both stratified flow and slug flow are stable. In this bi-stable flow regime, it is possible to observe stratified flow or regular hydrodynamic slug flow, depending on the inlet conditions. However, it is also possible to get one single slug at a time in the pipe. The distinctive characteristic of such “solitary” slugs is that they grow continuously as they travel along the pipe and therefore, in long pipelines, they can reach lengths up to thousands of pipe diameters and flood the downstream process installations. We first show how the length of solitary slugs can be predicted using slug tracking simulations. Based on those transient simulation results, we provide an explanation for the slug growth and we propose a simple quasi-steady-state model allowing us to predict the slug length in good agreement with the transient simulations. Finally, we explain how we can determine the boundaries of the bi-stable flow regime in which solitary slugs occur.

The cavitation flow can have a great impact on the projectile's water-exit attitude and stability. At present, the research on cavitation flow is mainly focused on the single projectile, while less research has been conducted on the cavitation flow of projectiles successively launched underwater. In this paper, a verification of the flow simulation method and validation of the cavitation model is presented. The multiphase flow associated with cavitation flows, interference characteristics of the cavitation vortex structure, and load characteristics of the projectiles successively launched underwater are studied. The results show that owing to the flow interference, the attitude of the projectile is deflected to the outside. A large-scale cavity shedding phenomenon of the inside cavity occurs under the incoming flow. A large number of small-scale vortex rings appear above the water surface in the projectile that successively exited the water. As the cavitation number of the projectiles launched successively decreases, the turbulent vortex structure is gradually enriched. In addition, both the inside and the outside are subject to extremely high peak collapse loads. Remarkably, the peak pulsating pressure generated by the collapse of the cavity is strongly correlated with the state of the cavity when the head of the projectile touches the water surface.

We studied the physical mechanism behind the bubble-elastic boundary interaction. In the present paper, three high-speed cameras were used to simultaneously test. Through digital image correlation technology, experimental data were obtained and analyzed, such as elastic boundary deformation. The results revealed that, due to the convex-concave deformation of the elastic boundary, the maximum collapse velocity occurred on both sides of the bubble wall. The deformation of the elastic boundary first increased and then decreased as the initial bubble-boundary distance decreased. We found that the convex deformation of the elastic boundary was exceptional, and nearby was gully, which greatly disturbed the flow field and thus affected the bubble collapse evolution. The boundary deformation velocity was in the shape of a ring, that is, the deformation was transmitted around the boundary in the form of a wave, diffusing energy. Overall, elastic boundary absorbed energy through its own convex-concave deformation, and this energy was transferred to the elastic boundary to alleviate the damage of cavitation bubbles.

Multiphase compressible flow systems can exhibit unsteady and fast-transient dynamics, marked by sharp gradients and discontinuities, and material boundaries that interact with the evolving flow. The transient nature of the dynamics presents challenges to employing artificial intelligence (AI) and data-driven models for predicting flow behaviors. In this study, we explore the potential of physics-aware recurrent convolutional neural networks (PARC) to model the spatiotemporal dynamics of multiphase flows in the presence of shocks and reaction fronts. PARC is a neural network model that incorporates the generic form of the diffusion–advection–reaction equation in its network architecture, which mimics the process of solving the governing equations of fluid flows. In contrast to physics-informed machine learning approaches such as physics-informed neural networks (PINNs) where models are trained to directly minimize the residual of governing equations, PARC takes a dynamical systems viewpoint and does not seek to minimize potentially nonconvex and nonlinear loss terms. To assess the ability of PARC to accurately learn and simulate the physics of multiphase flows, we train and test PARC on various flow simulation problems, including the Burgers’ equation, fluid flow behind a cylindrical cross-section, and unsteady shock interactions with a particle at varying Mach numbers. We analyze PARC’s performance and examine sources of error in its prediction, in terms of differentiation and integration schemes and different weighting strategies for the model update. Based on our observations, we discuss PARC’s capabilities and limitations in multiphase flow applications and propose future research directions.

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.