Machine Learning Augmented Two-Fluid Model for Segregated Flow

Segregated flow, including stratified and annular flows, is commonly encountered in several practical applications such as chemical, nuclear, refrigeration, and oil and gas industries. Accurate prediction of liquid holdup and the pressure gradient is of great importance in terms of system design and optimization. The current most widely accepted model for segregated flow is a physics-based two-fluid model that treats gas and liquid phases separately by incorporating mass and momentum conservation equations. It requires empirically derived closure relationships that have the limitation of being applicable only under a narrow range of input parameters under which they were developed. In this paper, we proposed a more generalized machine learning augmented two-fluid model, using a database that spans the range of various flowing conditions and fluid properties. Machine learning algorithms such as random forest, neural networks, and gradient boosting were tested for the best performing data-driven predictive model. The new model proposed in this work successfully captures the complex, dynamic, and non-linear relationships between the friction factor and flowing conditions. A comprehensive model evaluation against nineteen existing correlations shows the best results from the proposed model.

Influence of proppant physical properties on sand accumulation in hydraulic fractures

The proppant accumulation form in fractures is related to the formation conductivity after fracture closure, also closely related to the production rate of oil/gas wells. In order to investigate the influence of proppant physical properties on sand accumulation in fractures, a particle–fluid coupling flow model is established based on the Euler two-fluid model. Geometric parameters of a fracture in tight oil wells are approximately scaled in equal proportion as the physical model, which is solved by the finite volume method. And the model accuracy is verified by comparing with the physical experimental simulation in the literature. Results show that the higher proppant concentration corresponds to the faster particle sedimentation rate, and the greater sand embankment accumulation as well. However, the fluid viscosity will increase, inhibiting proppant migration to the deep part of the fracture. Reducing proppant density and particle size will enhance the fluidization ability of particles, which is conducive to the migration to the deep fracture at the initial stage of pumping. But, it is not beneficial to have a desirable accumulation state in the middle and later pumping stage, so it is difficult to obtain a higher comprehensive equilibrium height.

Modeling and Simulation of the Ion-Binding-Mediated Swelling Dynamics of Mucin-like Polyelectrolyte Gels

Volume phase transitions in polyeletrolyte gels play important roles in many biophysical processes such as DNA packaging, nerve excitation, and cellular secretion. The swelling and deswelling of these charged polymer gels depend strongly on their ionic environment. In this paper, we present an extension to our previous two-fluid model for ion-binding-mediated gel swelling. The extended model eliminates the assumptions about the size similarity between the network and solvent particles, which makes it suitable for investigating of a large family of biologically relevant problems. The model treats the polyeletrolyte gel as a mixture of two materials, the network and the solvent. The dynamics of gel swelling is governed by the balance between the mechanical and chemical forces on each of these two materials. Simulations based on the model illustrate that the chemical forces are significantly influenced by the binding/unbinding reactions between the ions and the network, as well as the resulting distribution of charges within the gel. The dependence of the swelling rate on ionic bath concentrations is analyzed and this analysis highlights the importance of the electromigration of ions and the induced electric field in regulating gel swelling.

Plasmon resonance at the interface dielectric - nanocomposite material with superconducting inclusions

This article theoretically considers surface plasmon resonance in composite structures. The features of the surface plasmon resonance arising at the interface with media containing nanoparticles from a high-temperature superconductor are investigated. The dielectric constant of spherical superconducting inclusions is considered taking into account Gorter-Casimir two-fluid model. The temperature dependence of the electrodynamic parameters of the superconductor is taken into account. The two-fluid model, the dependence of the concentration of non-superconducting electrons in a superconductor is often used as the fourth power of temperature nn~T4. In this work, a phenomenological model is used, according to which the electron concentration of non-superconducting electrons in a superconductor is determined by the formula nn~Tγ with γ=1.3÷2. This model is in good agreement with experimental data for high-temperature ceramic superconductors. The dispersion characteristics of surface plasmons arising in a planar structure with a thin nanocomposite superconductor layer are investigated. It is shown that the dispersion characteristics depend significantly on temperature.

Heat flux during boiling of superfluid helium inside a porous body based on a two-fluid model

The calculation of the recovery heat flux density is considered for superfluid helium boiling on the cylindrical heater inside porous structure. System of equations is based on the methods of continuum mechanics and molecular kinetic theory. The new type of boundary condition on the vapor-liquid interface based on the two-fluid model is formulated. Heat transfer in a free liquid is described by the Gorter-Mellink semi-empirical theory. Inside the porous structure the processes is discussed by the two-fluid model and filtration equation. Experimental data on the boiling of superfluid helium inside the porous structure are interpreted based on the formulated mathematical model. The qualitative and in some cases quantitative agreement between the calculated and experimental values of the recovery heat flux were obtained in the considered range of parameters