International Journal of Multiphase Flow最新文献

The mesh-dependency of the breakup of liquid films, including their breakup length scales and resulting drop size distributions, has long been an obstacle inhibiting the computational modeling of large-scale spray systems. With the aim of overcoming this barrier, this work presents a framework for the prediction and modeling of subgrid-thickness liquid film formation and breakup within two-phase simulations using the volume of fluid method. A two-plane interface reconstruction is used to capture the development of liquid films as their thickness decreases below the mesh size. The breakup of the film is predicted with a semi-analytical model that incorporates the film geometry captured through the two-plane reconstruction. The framework is validated against experiments of the bag breakup of a liquid drop at $\mathrm{We}=13.8$ through the comparison of the resulting drop size and velocity distributions. The generated distributions show good agreement with experimental results for drop resolutions as low as 25.6 cells across the initial diameter. The presented framework enables these drop breakup simulations to be performed at a computational cost three orders of magnitude lower than the cost of simulations utilizing adaptive mesh refinement.

Despite the enormous potential in facilitating natural development and migration of interfaces during multiphase simulation, the phase-field method remains restricted to low-density ratios, owing to inherent thermodynamic inconsistency, especially for multiphase flow systems with surfactants. The present paper first constructs a liquid-vapor phase transition phase-field model with soluble surfactants using the second law of thermodynamics as the original model. Then, a simplified liquid-vapor phase transition model with soluble surfactants that satisfies thermodynamic consistency is proposed to simulate pool boiling at higher-density ratio. A novel numerical algorithm for the simplified model that satisfies semi-discrete thermodynamic consistency is also developed. Compared with the original model, the thermodynamically consistent characteristics of the simplified numerical model proposed in this paper can significantly reduce the spurious velocity on the interface of a static droplet and thus enable the numerical model to simulate liquid-vapor transition at higher liquid/vapor density ratios. Vapor-liquid coexistence, Laplace's law, and multiple bubble coalescence are used to validate the accuracies and effectiveness of the mathematical model and numerical algorithm. The liquid/vapor density ratio can reach 6776:1 under saturation temperature 0.3T_c (T_c is the critical temperature). The approach is then used to model pool boiling at a low saturation temperature (0.5T_c) with and without soluble surfactants, significantly lower than reported in comparable literature. The results demonstrate that surfactants significantly influence the dynamics of bubbles, and a critical concentration can be identified. In addition, soluble surfactants can also suppress coalescence between adjacent bubbles and prevent the formation of larger bubbles during pool boiling.

Experimental and numerical studies on charge transport and liquid atomization with the consideration of electrohydrodynamics (EHD) have been performed for a high-speed rotary bell atomizer with internal charging system. The VOF-to-DPM hybrid model in the commercial CFD code ANSYS Fluent is used to investigate and analyse the liquid breakup. Furthermore, the charge conservation equation is solved not only considering flow convection but also the significant ion drift convection due to the presence of the strong electric field. We introduce the so-called apparent ion mobility coefficient that depends on the permittivity and conductivity of liquid, the film thickness on the bell surface and the electric field strength. With this model we can calculate the charge migration from the electrode, in this case the bell surface, to the liquid film and the droplets. Simulation results show an inhomogeneous charge distribution perpendicular to the bell surface, namely charge accumulating mainly on the film surface. Breakup simulations are carried out using a Newtonian liquid and a real paint. The electric body forces have been included in the Navier-Stokes equations. Effects of EHD on the liquid breakup are analysed. The relationship of droplet charge to droplet diameter is obtained, from which the total current is predicted that compared well with experiments. Simulation results deliver useful information for an improved understanding of the relevant physical processes.

Rectangular jets exhibit axis-switching behavior which results in enhanced flow entrainment compared to round jets. This feature allows for their potential industrial use as passive flow controllers in mixing applications. However, rectangular jets have received limited attention compared to round jets. To operate rectangular jets optimally, a better understanding on the underlying phenomena influencing the axis-switching of the jet is required. In this paper, Direct Numerical Simulations of rectangular jets are performed at different injection velocities using the Local Front Reconstruction Method (LFRM) to track the liquid–gas interface. The simulations are validated using experiments in a similar range of Weber and Reynolds numbers. The obtained results showed that LFRM can accurately capture the jet oscillations, break-up lengths and droplet sizes observed experimentally. Additionally, a fully developed velocity profile at the nozzle outlet enhances the jet stability resulting in larger break-up length values compared to a uniform velocity profile.

This work presents the development of a novel solver tailored for simulating multiphase flows within heterogeneous porous media. Leveraging the Eulerian multi-fluid model coupled with Darcy’s law, the solver demonstrates adaptability across diverse scales, effectively handling heterogeneous porosity and permeability fields. The proposed solver, called upstreamFoam, extends the capabilities of OpenFOAM framework, specifically the multiphaseEulerFoam, by incorporating models for porous media simulations. This integration introduces new features and formulations, allowing for the simulation of compressible multiphase flows in porous media with intricate properties. The approach presented here provides a robust framework for characterizing reservoirs and treating heterogeneous porous systems at different scales. A successful validation of the introduced solver for classical problems with analytical, semi-analytical, and reference solutions is presented. Then, applications on a wide range of multiphase flows in heterogeneous porous media at different scales have been studied, demonstrating the potential of the solver to simulate complex multiphase problems.

Fluid Dynamics is a key scientific field to multitudes of engineering applications. Experimental work in this field requires careful set-up and expensive image-capturing equipment, particularly when considering the finer details of complex phenomena. In this work, we study the application of super-resolution Generative Adversarial Networks (GANs) to achieve high-resolution results by upscaling lower-resolution experimental images.

We train GANs proposed for natural images on a bubbly flow experimental Fluid Dynamics dataset and compare common super-resolution evaluation metrics to domain expert assessments of the upscaled images. We find that these models achieve promising results, as evaluated by experts, and transfer learning from natural images translates to better performance overall. Attention mechanisms are found to be particularly useful in recreating sharper details. On the other hand, traditional super-resolution evaluation metrics are found to align poorly with expert perception of quality, signaling the need for better systematic evaluation methodologies in this domain.

A theoretical model for describing the sequential splitting of droplets flowing through the fractal tree-shaped microchannel network with arbitrary branch level is developed to explore the mechanisms underlying the hydraulic imbalance on the high-throughput droplets production. Accordingly, detailed droplet splitting characteristics are presented, including the droplet velocities in branches, droplet distribution coefficient, and monodispersity of droplets production. It is found that the uniformity of droplet mainly depends on two key dimensionless parameters, namely Λ₁ and Λ₂, where Λ₁ is determined by the initial working condition involving the initial lengths and viscosity of the continuous and discrete phases, the width of the 0th level channel, and the initial capillary number, and Λ₂ is concerned with the outlet pressure p_{out, [2}^n-1_] and the pressure drops of the continuous and discrete phases at the 0th level channel. The monodispersity of droplets goes down with the decreasing Λ₁ and the increasing Λ₂. Based on the Λ₁ and Λ₂, the optimal design strategies contributing to enhancing the droplet generation uniformity are recommended, including increasing Ca, enlarging the length of continuous phase flow at the main channel, and increasing the lengths of each level channels. Furthermore, the tree-shaped microchannel networks with higher branch level (n) have stronger ability to resist asymmetric disturbances. In particular, in our work, the width fractal dimension Δ = 2 is adopted as a proper key structure parameter, so as to ensure sequential breakup of droplet at each T-junction under symmetric condition.

We highlight the work of a multi-university collaborative programme, PREMIERE (PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems), which is at the intersection of multi-physics and machine learning, aiming to enhance predictive capabilities in complex multiphase flow systems across diverse length and time scales. Our contributions encompass a variety of approaches, including the Design of Experiments for nanoparticle synthesis optimisation, Generalised Latent Assimilation models for drop coalescence prediction, Bayesian regularised artificial neural networks, eXtreme Gradient Boosting for microdroplet formation prediction, and a sub-sampling based adversarial neural network for predicting slug flow behaviour in two-phase pipe flows. Additionally, we introduce a generalised latent assimilation technique, Long Short-Term Memory networks for sequence forecasting mixing performance in stirred and static mixers, active learning via Bayesian optimisation to recover coalescence model parameters for high current density electrolysers, Gaussian process regression for drop size distribution predictions for sprays, and acoustic emission signal inversion using gradient boosting machines to characterise particle size distribution in fluidised beds. We also offer perspectives on the development of a shape optimisation framework that leverages the use of a multi-fidelity multiphase emulator. The results presented have applications in chemical synthesis, microfluidics, product manufacturing, and green hydrogen generation.

Different air phase regimes are formed by controlled air injection in a spatially developing flat plate turbulent boundary layer (TBL). The air is introduced via a slot type injector without the use of a backward-facing step or cavitator upstream of the air injection position. The effect of different incoming liquid flow characteristics on the different regimes is investigated by varying both the liquid freestream velocity and the incoming TBL thickness. The latter is realized through changing the position of the air injection along the length of the water tunnel facility. That resulted in a downstream distance based Reynolds number from 1 to 5 million. Three different air phase regimes are identified under different air flow rates and freestream velocities: the bubbly regime, the transitional, and the air layer regime. The morphological differences of each one are described and quantitative analysis is performed based on the non-wetted area in each condition. The incoming TBL as well as the flow around the air layer are measured with planar particle image velocimetry. The latter enabled the determination of the air layer thickness. In addition, the ratio of the air layer to the incoming boundary layer thickness $t_{air}/\delta$ is also calculated ($\approx$ 0.04 – 0.5). This is a significant dimensionless parameter for scaling, which indicates the extent to which the air layer is embedded within the incoming TBL. Depending on the incoming flow conditions, a two or three branch air layer is formed. The length of the air layer is found to increase with increasing liquid freestream velocities. A good agreement between the air layer length and a half gravity wave predicted by the dispersion relation is found. An increase of the air layer length is observed with a decreasing incoming TBL thickness. This is attributed to a decrease in the local mean velocity at the air–water interface due to the TBL growth. Finally, increasing the incoming TBL thickness delays the onset of the air layer regime.