Search results

The purpose of this paper is to investigate oil-gas slug formation in horizontal straight pipe and its associated pressure gradient, slug liquid holdup and slug frequency.

The abrupt change in gas/liquid velocities, which causes transition of flow patterns, was analyzed using incompressible volume of fluid method to capture the dynamic gas-liquid interface. The validity of present model and its methodology was validated using Baker’s flow regime chart for 3.15 inches diameter horizontal pipe and with existing experimental data to ensure its correctness.

The present paper proposes simplified correlations for liquid holdup and slug frequency by comparison with numerous existing models. The paper also identified correlations that can be used in operational oil and gas industry and several outlier models that may not be applicable.

The correlation may be limited to the range of material properties used in this paper.

Numerically derived liquid holdup and holdup frequency agreed reasonably with the experimentally derived correlations.

The models could be used to design pipeline and piping systems for oil and gas production.

The paper simulated all the seven flow regimes with superior results compared to existing methodology. New correlations derived numerically are compared to published experimental correlations to understand the difference between models.

The paper aims to study the effect of liquid flow velocity on corrosion behavior of 20# steel at initial stage under (CO2/aqueous solution) gas–liquid two-phase plug flow conditions.

Weight loss, scanning electron microscopy, energy-dispersive X-ray spectroscopy and XPS methods were used in this study.

The corrosion rate increased with the increasing liquid flow velocity at any different corrosion time. The corrosion rate decreased with the extension of corrosion time at the same liquid flow velocity. There was no continuous corrosion products film on the whole pipe wall at any different corrosion time. The macroscopic brown-yellow corrosion products on the pipe wall surface decreased with the increasing liquid flow velocity and the loose floccus corrosion products decreased gradually until these products were transformed into un-continuous needle-like dense products with the increasing liquid velocity. The main elements among the products film were Fe, C and O, and the main phases of products film on the pipe wall were Fe3C, FeCO3, FeOOH and Fe3O4. When the corrosion time was 1 h under different liquid–velocity condition, the thickness of local corrosion products film was from 3.5 to 3.8 µm.

The ion mass transfer model of corrosion process in pipe was put forward under gas–liquid two-phase plug flow condition. The total thickness of diffusion sublayer and turbulence sublayer decreased as well as the turbulence propagation coefficient increased with the increasing liquid velocity, which led to the increasing velocity of ion transfer during corrosion process. This was the fundamental reason for the increase of corrosion rate with the increasing liquid velocity.

This paper aims to explore the effectiveness and mechanism of a droplet-laden flow in a microfluidic system.

Numerical approach based on the volume of fluid method is implemented for modelling the forced heat transport in a droplet-laden flow in a microchannel.

The heat transfer effectiveness of droplet-laden flow is found to be obviously superior to that of a single-phase flow because of the circulation stream between the droplets. In addition, the effectiveness will be further increased when an elongated droplet is being laden because the circulation streams within and between the droplets are more pronounced. The elongated droplet size affects the heat transfer characteristics signified by Nusselt number, and there exists an optimum value at a fixed parameter.

This paper attempts to clarify the influence on the heat transfer performance when droplet with various shape and size being laden. This work is done by none before. This research work applies a solid foundation for designing a cooling system in microelectromechanical system.

The purpose of this paper is to propose a prediction method of gas-liquid two-phase flow patterns and reveal the flow characteristics in the suction chamber of a centrifugal pump.

A transparent model pump was experimentally studied, and the gas-liquid two-phase flow in the pump was numerically simulated based on the Eulerian–Eulerian heterogeneous flow model. The numerical simulation method was verified from three aspects: the flow pattern in the suction chamber, the gas spiral length and the external characteristics of the pump. The two-phase flow in the suction chamber was studied in detail by using the numerical simulation method.

There are up to eight flow patterns in the suction chamber. However, at a certain rotational speed, only six flow patterns are observed at the most. At some rotational speeds, only four flow patterns appear. The gas spiral length has little relationship with the gas flow rate. It decreases with the increase of the liquid flow rate and increases with the increase of the rotational speed. The spiral flow greatly increases the turbulence intensity in the suction chamber.

A method for predicting the flow pattern was proposed. Eight flow patterns in the suction chamber were identified. The mechanism of gas-liquid two-phase flow in the suction chamber was revealed. The research results have reference values for the stable operation of two-phase flow pumps and the optimization of suction chambers.

The purpose of this paper is to explore gas/liquid two-phase flow is widely existed in industrial fields, especially in chemical engineering. Electrical resistance tomography (ERT) is considered to be one of the most promising techniques to monitor the transient flow process because of its advantages such as fast respond speed and cross-section imaging. However, maintaining high resolution in space together with low cost is still challenging for two-phase flow imaging because of the ill-conditioning of ERT inverse problem.

In this paper, a sparse reconstruction (SR) method based on the learned dictionary has been proposed for ERT, to accurately monitor the transient flow process of gas/liquid two-phase flow in a pipeline. The high-level representation of the conductivity distributions for typical flow regimes can be extracted based on denoising the deep extreme learning machine (DDELM) model, which is used as prior information for dictionary learning.

The results from simulation and dynamic experiments indicate that the proposed algorithm efficiently improves the quality of reconstructed images as compared to some typical algorithms such as Landweber and SR-discrete fourier transformation/discrete cosine transformation. Furthermore, the SR-DDELM has also used to estimate the important parameters of the chemical process, a case in point is the volume flow rate. Therefore, the SR-DDELM is considered an ideal candidate for online monitor the gas/liquid two-phase flow.

This paper fulfills a novel approach to effectively monitor the gas/liquid two-phase flow in pipelines. One deep learning model and one adaptive dictionary are trained via the same prior conductivity, respectively. The model is used to extract high-level representation. The dictionary is used to represent the features of the flow process. SR and extraction of high-level representation are performed iteratively. The new method can obviously improve the monitoring accuracy and save calculation time.

The purpose of this study is to solve convective diffusion equation analytically by considering appropriate boundary conditions and using the Taylor-Aris method to determine the solute concentration, the effective and relative axial diffusivities.

>An analysis has been conducted on how body acceleration affects the dispersion of a solute in blood flow, which is known as a Bingham fluid, within an artery. To solve the system of differential equations analytically while validating the target boundary conditions, the blood velocity is obtained.

The blood velocity is impacted by the presence of body acceleration, as well as the yield stress associated with Casson fluid and as such, the process of dispersing the solute is distracted. It graphically illustrates how the blood velocity and the process of solute dispersion are affected by various factors, including the amplitude and lead angle of body acceleration, the yield stress, the gradient of pressure and the Peclet number.

It is witnessed that the blood velocity, the solute concentration and also the effective and relative axial diffusivities experience a drop when either of the amplitude, lead angle or the yield stress rises.

The purpose of this paper is to numerically investigate the heat transfer enhancement in a tube filled partially with porous media under non-uniform porosity distribution and thermal dispersion effects. The optimum porous thickness ratio [R_(r,Nu)] for the heat transfer enhancement under these conditions with and without considering required pumping power is evaluated.

The local thermal non-equilibrium and Darcy–Brinkman–Forchheimer models are used to simulated thermal and flow fields in porous region. The tube wall and flow regime are assumed to be isothermal and laminar, respectively. The impacts of Darcy number (Da = 10^-6 - 10^-1) and inertia parameter (F = 0 − 2) on the Nusselt number and friction factor are studied for non-uniform porosity distribution.

First, the effect of Nusselt number indicates that there are two different behaviors with respect to uniform and non-uniform porosity for partially and fully filled porous pipe. Second, variable porosity in porous region has significant influence on the optimum thickness ratio with considering required pumping power. For negligible inertia term, it depends on the Darcy number, whereas it is 0.9 at F > 1. Third, the plug flow assumption cannot be valid even at lower Darcy number under non-uniform porosity, while this assumption is applicable at Da < 10^-3 for constant porosity distribution in porous region.

According to the best knowledge of authors, the optimum porous thickness ratio for the heat transfer enhancement considering the pressure loss effects under variable porosity has not reported up to now. Also the plug flow assumption in such physics is not discussed.

This paper aims to discuss flow pattern transition (FPT) as an important factor in multiple-phase flow measurements. Several methods have been proposed to control FPT, but those methods fail to address the many issues in complex flow conditions that can affect flow patterns.

In this paper, a non-intrusive sensor instrumentation is applied to extract measurable data under different flow conditions. Using these data, a simple theoretical–mathematical method along with an orthogonal design is applied to FPT optimization. Orthogonal experiments are designed and carried out according to theoretical guidelines. Three selected process parameters – phase fraction, gas pressure in the initial independent process and liquid speed – are optimized for FPT results to produce a minimum FPT time.

The following results are obtained: the phase fraction in the initial independent process can lead to significant reductions in FPT time, gas pressure plays an important role and liquid speed has no apparent effect on FPT results. Under optimized conditions, FPT time can be shortened to 0.3-0.6 times by controlling the above three parameters compared with normal conditions.

The proposed method is simple, rapid and efficient for evaluating an FPT process and lays the foundation for further FPT applications.

This paper aims to introduce modeling, numerical simulation and convergence analysis of the problem of nanoparticles’ transport carried by a two-phase flow in a porous medium. The model consists of equations of pressure, saturation, nanoparticles’ concentration, deposited nanoparticles’ concentration on the pore-walls and entrapped nanoparticles concentration in pore-throats.

A nonlinear iterative IMPES-IMC (IMplicit Pressure Explicit Saturation–IMplicit Concentration) scheme is used to solve the problem under consideration. The governing equations are discretized using the cell-centered finite difference (CCFD) method. The pressure and saturation equations are coupled to calculate the pressure, and then the saturation is updated explicitly. Therefore, the equations of nanoparticles concentration, the deposited nanoparticles concentration on the pore walls and the entrapped nanoparticles concentration in pore throats are computed implicitly. Then, the porosity and the permeability variations are updated.

Three lemmas and one theorem for the convergence of the iterative method under the natural conditions and some continuity and boundedness assumptions were stated and proved. The theorem is proved by induction states that after a number of iterations, the sequences of the dependent variables such as saturation and concentrations approach solutions on the next time step. Moreover, two numerical examples are introduced with convergence test in terms of Courant–Friedrichs–Lewy (CFL) condition and a relaxation factor. Dependent variables such as pressure, saturation, concentration, deposited concentrations, porosity and permeability are plotted as contours in graphs, whereas the error estimations are presented in a table for different values of the number of time steps, number of iterations and mesh size.

The domain of the computations is relatively small; however, it is straightforward to extend this method to the oil reservoir (large) domain by keeping similar definitions of CFL number and other physical parameters.

The model of the problem under consideration has not been studied before. Also, both solution technique and convergence analysis have not been used before with this model.

The use of pneumatic conveying of solid bulk over long distance has become a popular technique due to low operational cost, low maintenance requirement, layout flexibility and ease of automation. The purpose of this paper is to identifity the flow regime in a pneumatic conveyor system by electrodynamic sensor placed around the pipe using fuzzy logic tools.

Electrical charge tomography is used to detect the existence of inherent charge on the moving particles through the pipe. Linear back projection algorithm and filtered back projection algorithm are employed to produce tomography image. Baffles of different shapes are inserted to create various flow regimes, such as full flow, three quarter flow, half flow and quarter flow. Fuzzy logic tools are used to identify different flow regimes and produce filtered back concentration profiles for each flow regime.

The results show significant improvement in the pipe flow image resolution and measurement.

This paper presents a flow identifier method using electrical charge tomography and fuzzy logic to monitor solid particles flow in pipeline.