Dynamic Viscosity Ratio Research Articles

Slip boundary condition near the wall-interface contact line in axial stratified two-phase flow

The behavior of the velocity and shear stresses in two-phase laminar stratified flow near a triple point (TP), formed in the flow cross-section by the intersection of the interface with the conduit wall, is reconsidered. Differently from the no-slip boundary condition that showed a possibility of diverging shear stresses upon approaching the TP, we allow a slip of the fluids at the wall that can be prominent in the TP region. The Navier's boundary condition is used, which considers a linear relationship between the slip velocity and the strain rate component perpendicular to the surface. The solution for the velocity field in the TP region is obtained in terms of a power series of the distance from the TP having a discrete set of powers. Similarly to the solution obtained with no-slip B.C., a so-called ‘characteristic equation’ is obtained. Its solution yields a discrete set of non-integer powers that are dependent on the dynamic viscosity ratio and the contact angle. However, contrary to the no-slip solution, with Navier's B.C, each of these powers introduces a tower of terms resulting from the relation between the slip velocity and the velocity derivative at the wall. In addition, the solution also includes a tower of integer powers. The solution yields the velocity and the shear stress fields, as well as the flux of the force per length that acts on an arbitrary surface in the flow field. The latter is obtained by considering an equivalent 2D representation of the stress tensor. These are examined in comparison to the corresponding results obtained when no-slip at the wall is imposed. The relaxation of the wall shear stresses in cases where the no-slip condition predicts diverging wall shear stresses at the TP is demonstrated. It is shown that if the local velocity in the TP region is a limit of a global no-slip solution, the scaled velocity field in the TP region is independent of the details of the global flow field.

Electrokinetic Effect of a Two-Liquid Interface within a Slit Microchannel.

This paper presents an investigation of the electrokinetic effect at a two-liquid (immiscible liquid-aqueous solution) interface within a slit microchannel using a three-dimensional (3D) numerical model, with a particular focus on the impact of the surface ζ-potential and liquid phase height on the interface electrokinetic velocity. The findings indicate that the direction of the interface movement depends on the ζ-potentials at the two-liquid interface and the microchannel wall. When the absolute value of the negative ζ-potential at the interface is smaller than that at the wall, the interface moves toward the negative pole of the applied direct current (DC) electric field; conversely, it moves in the opposite direction. The velocity of interface motion decreases as the height of the aqueous phase and the dynamic viscosity ratio between the immiscible liquid and the aqueous solution increase. Conversely, the velocity increases with an elevation in the height of the immiscible liquid phase and the DC electric field intensity. This study holds significant importance in elucidating the patterns of change in fluid interface electrokinetic effects and their potential applications in manipulating and separating particulate pollutants within water systems.

Нарушение закона броуновской релаксации для частиц феррита кобальта в воде

In the temperature range 0–90°C, the dynamic susceptibility of three samples of a magnetic fluid based on cobalt ferrite particles stabilized in water with a double layer of a surfactant was meas-ured. The first layer of the stabilizer was formed of auric acid molecules. The second layer consisted of a mixture of lauric acid and sodium dodecyl sulfate. The liquid samples had a small (about 10%) volume fraction of particles in order to reduce the influence of interparticle interactions and eliminate non-Newtonian rheological properties. The main parameter in which the samples differed was viscosity. It was changed by adding a small amount of polyvinyl alcohol. For all samples, in the studied temperature range the frequency dependence of the dynamic susceptibility had a quasi-Debye form with a pronounced maximum for the imaginary part. The value of the magnetization relaxation time was determined from the frequency of the maximum on the imaginary part of the dynamic susceptibility. As a result, the dependences of themagnetization relaxation time on tem-perature were obtained. To analyze the results obtained, viscosities of the samples were measured. All samples exhibited the properties of Newtonian fluids –the value of dynamic viscosity did not depend on the shear rate. The obtained results on the dynamic susceptibility and viscosity were compared by plotting relaxation times as a function of the ratio ofdynamic viscosity to absolute temperature. The resulting dependences do not fit on one universal straight line, as it is supposed to be according to the theory. The actual graph looks like a family of three different curves that di-verge as viscosity increases. In order to assess the influence of Néel relaxation on the resulting sus-ceptibility, the dynamic susceptibility of a frozen sample of the magnetic fluid was measured. The resulting susceptibility value was about 3% of the initial susceptibility of the liquid sample. Thus, despite the insignificant contribution of the Néel mechanism of magnetization relaxation to the dy-namic susceptibility, it is impossible to explain the obtained measurement results on the basis of the Brownian relaxation mechanism alone.

Computational fluid dynamics simulations of Taylor bubbles rising in vertical and inclined concentric annuli

Motivated by a dearth of research on the dynamics of single Taylor bubbles in annular conduits, a computational study of Taylor bubbles rising in vertical and inclined annuli is performed using a three-dimensional computational fluid dynamics (CFD) simulation with the Volume-of-Fluid (VOF) method implemented in the commercial software ANSYS Fluent (Release 19.2). The effects of Eötvös number (Eo = [10, 300]), inverse viscosity number (Nf = [40, 320]), and inclination angles (θ = {10°, 20°, 30°,…, 80°}) on the steady-state Taylor bubble shape and rise velocity are investigated. The latter is parameterized by Froude number (Fr) and simulations are carried out keeping constant liquid-gas density ratio and dynamic viscosity ratio at 1000 and 100, respectively. The simulation results provide good agreement with the existing numerical findings and experimental observations. For Taylor bubbles in a vertical annulus, the surface tension and liquid viscosity show significant impacts on bubble shape (length and trailing edge) and Fr for Eo = [10, 100] and Nf = [40, 160]. A correlation for Fr in terms of Eo and Nf is proposed and compared against 66 numerical simulations and 20 air-water experimental results available in the literature, resulting in average errors of 2.13% and 5.52%, respectively. Relatively large errors of 7.38% for characteristic dimension D* ≤ 45 mm and 11.82% for D* ≥ 344.9 mm are observed (D* = Do + Di). The correlation exhibits improved performance with an average error of 3.5% for 45 mm ≤ D* ≤ 214 mm relative to the only existing model. The shape of bubbles and Fr values in inclined annulus, where the bubble becomes more streamlined and unfolded, are observed to be dramatically different from those in vertical annulus. Interestingly, the wrap angle (θwrap) decreases linearly with the increase of inclination angle. Predictions of the dimensionless rise velocity in inclined annulus are made and successfully compared with an existing model and experimental data from the literature.

Evaporation and fluid flow near the boundary of a stationary dry patch.

We consider an isolated circular dry patch formed in an evaporating liquid layer and investigate local viscous flows in both liquid and air near the contact line which is the boundary of the dry patch. Flow patterns in the liquid deviate significantly from the predictions of single-phase models even when the air-to-liquid dynamic viscosity ratio is small. In particular, the separatrices in the liquid flow patterns at large contact angles disappear completely for a range of realistic viscosity ratios when the shear stress on the air side of the interface is accounted for. Experimentally observed motion of microdroplets near the contact line under combined action of gravity and moist air flow is described using our local flow model. We demonstrate that analysis of droplet trajectories leads to unambiguous determination of the local evaporative flux profile. A numerical finite-element approach for the steady diffusion equationis then used to extract the same flux profile from the global solution for concentration field in the limiting case of very thin liquid layer and small contact angle. The local evaporation rate is underpredicted by the numerical method, most likely due to the neglect of convective mass transfer in the air.

Study on co-injection molding of poly(styrene-ethylene-butylene-styrene) and polypropylene: Simulation and experiment

In this paper, poly(styrene-ethylene-butylene-styrene) (SEBS) triblock copolymer blends were used as the soft skin material and polypropylene (PP) was used as the hard core for co-injection molding. The effect of different SEBS thermoplastic elastomer skin materials on the filling state of the core layer of the co-injection sample was analyzed, and the co-injection molding was evaluated by the filling factor and shape distribution factor. When the core material flows at the matched skin interface, the core layer gradually changes from an uneven finger-like flow front to a smooth flow, and the shape distribution factor increases greatly. Both simulation and experimental results show that the shape distribution factor can correctly evaluate the filling effect of co-injection, and the corresponding samples have uniform skin-core interface, good compatibility and maximum skin thickness. According to the change of shearing rate, a dynamic viscosity ratio method was established to evaluate the co-injection process. When the dynamic viscosity ratio of the core/skin material is greater than and close to 1, the movement of the molecular chains on the interface matches, the flow front is smooth and the shape distribution factor is high. By changing the injection temperature of the material to adjust the dynamic viscosity ratio, the optimization of co-injection can also be achieved. The dynamic viscosity ratio method can be used to guide the flow forming and interface interaction analysis of heterogeneous materials.

Void Fraction Measurement Using the Coaxial Line Phase Sensor in the Vertical Gas-Liquid Slug Flow

Void fraction is one of the most important parameters in gas-liquid two-phase flow, which plays a crucial role in the pressure gradient calculation and the flow pattern analysis. In this paper, a new coaxial line phase sensor based on the electromagnetic wave propagation is designed and phase shift principle is proposed for the void fraction measurement, and the function relationship between the void fraction and phase difference is derived. By the theoretical analysis and 56 static calibration experiments, the measurement model is proposed in this paper. Air-water two-phase flow experiments have been conducted in a vertical tube at 48 flow conditions in a stainless-steel tubular test section which has an inside diameter of 50.0mm. The dimensionless quantities related to the void fraction, e.g. dynamic viscosity ratio, gas-liquid density ratio, gas-phase Froud number (Frg) and Lockhart-Martinelli parameter ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mathrm {X}}_{{\mathrm {LM}}}$ </tex-math></inline-formula> ), are dimensional analyzed. According to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Pi $ </tex-math></inline-formula> theorem, a new void fraction correlation which could acceptably handle all the available data of different flow conditions (authors’ and literature) is proposed. Laboratory results indicate that the mean absolute error (MAE) of the correlation is 6.46% within an error band of ±10% and 8.03% (183 literature data points) within an error band of ±15%. The void fraction correlation has good prediction accuracy and a certain extrapolation for different flow regimes and fluid characteristic parameters.

Study of Fingering Dynamics of Two Immiscible Fluids in a Homogeneous Porous Medium with Considering Wettability Effects Using a Pore-Scale Multicomponent Lattice Boltzmann Model

In the present study, a pore-scale multicomponent lattice Boltzmann method (LBM) is employed for the investigation of the immiscible-phase fluid displacement in a homogeneous porous medium. The viscous fingering and the stable displacement regimes of the invading fluid in the medium are quantified which is beneficial for predicting flow patterns in pore-scale structures, where an experimental study is extremely difficult. Herein, the Shan-Chen (S-C) model is incorporated with an appropriate collision model for computing the interparticle interaction between the immiscible fluids and the interfacial dynamics. Firstly, the computational technique is validated by a comparison of the present results obtained for different benchmark flow problems with those reported in the literature. Then, the penetration of an invading fluid into the porous medium is studied at different flow conditions. The effect of the capillary number (Ca), dynamic viscosity ratio (M), and the surface wettability defined by the contact angle (θ) are investigated on the flow regimes and characteristics. The obtained results show that for M&lt;1, the viscous fingering regime appears by driving the invading fluid through the pore structures due to the viscous force and capillary force. However, by increasing the dynamic viscosity ratio and the capillary number, the invading fluid penetrates even in smaller pores and the stable displacement regime occurs. By the increment of the capillary number, the pressure difference between the two sides of the porous medium increases, so that the pressure drop Δp along with the domain at θ=40∘ is more than that of computed for θ=80∘. The present study shows that the value of wetting fluid saturation Sw at θ=40∘ is larger than its value computed with θ=80∘ that is due to the more tendency of the hydrophilic medium to absorb the wetting fluid at θ=40∘. Also, it is found that the magnitude of Sw computed for both the contact angles is decreased by the increment of the viscosity ratio from Log(M)=−1 to 1. The present study demonstrates that the S-C LBM is an efficient and accurate computational method to quantitatively estimate the flow characteristics and interfacial dynamics through the porous medium.

Thermal conductivity and dynamic viscosity of mono and hybrid organic- and synthetic-based nanofluids: A critical review

Abstract Thermal conductivity and dynamic viscosity are two critical properties of nanofluids that indicate their heat transfer performance and flow. Nanofluids are prepared by dispersing mono or several organic or synthetic nanoparticles in selected base fluids to form mono or hybrid nanofluids. The qualitative and quantitative stability measurement of nanofluids will then be addressed, followed by a detailed discussion on how the dispersion of nanoparticles in water (W), ethylene glycol (EG), and the mixture of W:EG 60:40% by volume affects the thermal conductivity and dynamic viscosity ratio. The data comparison demonstrated that the thermal conductivity ratio increases with increasing normalized concentrations, the bulk temperature of nanofluids, and the smaller nanoparticle size. The dynamic viscosity ratio is multiplied by the normalized concentration increase. Nevertheless, as the bulk temperature climbed from 0 to 80°C, the dynamic viscosity ratio was scattered, and the dynamic viscosity ratio trend dropped with increasing particle size. While the majority of nanofluids enhanced thermal conductivity ratio by 20%, adding carbon-based nanoparticles to synthetic nanofluid increased it by less than 10%. The disadvantage of nanofluids is that they multiply the dynamic viscosity ratio of all nanofluids, which increase power consumption and reduces the efficiency of any mechanical system.

Comparative study of multicomponent Lattice Boltzmann models for binary mixture flows

Two lattice Boltzmann method (LBM) models for binary mixture flows are numerically compared. The first model solves the Navier–Stokes equations within the incompressible limit and considers the mixture as one single fluid. A multi relaxation time (MRT) collision operator tunes the fluid diffusivity independently of the fluid viscosity. The second model emerges from a different theoretical derivation of the kinetic theory, where the governing equations are recovered for each species of the mixture. A source term in the LBM defines the interspecies friction force and couples the species of the mixture. A pure diffusion flow and a 2D plane Poiseuille binary mixture flow verify both models in the incompressible limit where diffusive and viscous transport occurs. The influence of molecular mass ratio, dynamic viscosity ratio, and Schmidt number on species and mixture flow behavior is investigated. The numerical results show good agreement against their respective analytical solutions and capture the deviation between the velocity profiles according to the flow regime. The present numerical study underlines the difference between the models as a function of the flow regimes which was observed from the macroscopic governing equations.

Linear stability analysis of a Newtonian ferrofluid cylinder surrounded by a Newtonian fluid

We performed a linear stability analysis of a Newtonian ferrofluid cylinder surrounded by a Newtonian non-magnetic fluid in an azimuthal magnetic field. A wire is used at the centre of the ferrofluid cylinder to create this magnetic field. Isothermal conditions are considered and gravity is ignored. An axisymmetric perturbation is imposed at the interface between the two fluids and a dispersion relation is obtained allowing us to predict whether the flow is stable or unstable with respect to this perturbation. This relation is dependent on the Ohnesorge number of the ferrofluid, the dynamic viscosity ratio, the density ratio, the magnetic Bond number, the relative magnetic permeability and the dimensionless wire radius. Solutions to this dispersion relation are compared with experimental data from Arkhipenko et al. (Fluid Dyn., vol. 15, issue 4, 1981, pp. 477–481) and, more recently, Bourdin et al. (Phys. Rev. Lett., vol. 104, issue 9, 2010, 094502). A better agreement than the inviscid theory and the theory that only takes into account the viscosity of the ferrofluid is shown with the data of Arkhipenko et al. (Fluid Dyn., vol. 15, issue 4, 1981, pp. 477–481) and those of Bourdin et al. (Phys. Rev. Lett., vol. 104, issue 9, 2010, 094502) for small wavenumbers.

A Pseudopotential Lattice Boltzmann Method for Simulation of Two-Phase Flow Transport in Porous Medium at High-Density and High–Viscosity Ratios

In this work, the capability of a multiphase lattice Boltzmann method (LBM) based on the pseudopotential Shan-Chen (S-C) model is investigated for simulation of two-phase flows through porous media at high-density and high–viscosity ratios. The accuracy and robustness of the S-C LBM are examined by the implementation of the single relaxation time (SRT) and multiple relaxation time (MRT) collision operators with integrating the forcing schemes of the shifted velocity method (SVM) and the exact difference method (EDM). Herein, two equations of state (EoS), namely, the standard Shan-Chen (SC) EoS and Carnahan-Starling (CS) EoS, are implemented to assay the performance of the numerical technique employed for simulation of two-phase flows at high-density ratios. An appropriate modification in the forcing schemes is also used to remove the thermodynamic inconsistency in the simulation of two-phase flow problems studied at low reduced temperatures. The comparative study of these improvements of the S-C LBM is performed by considering an equilibrium state of a droplet suspended in the vapor phase. The solver is validated against the analytical coexistence curve for the liquid-vapor system and the surface tension estimation from the Laplace Law. Then, according to the results obtained, a conclusion has been made to choose an efficient numerical algorithm, including an appropriate collision operator, a realistic EoS, and an accurate forcing scheme, for simulation of multiphase flow transport through a porous medium. The patterns of two-phase flow transport through the porous medium are predicted using the present numerical scheme in different flow conditions defined by the capillary number and the dynamic viscosity ratio. The results obtained for the nonwetting phase saturation, penetration structure of the invading fluid, and the displacement patterns of two-phase flow in the porous medium are comparable with those reported in the literature. The present study demonstrates that the S-C LBM with employing the MRT-EDM scheme, CS EoS, and the modified forcing scheme is efficient and accurate for estimation of the two-phase flow characteristics through the porous medium.

Experimental studies and ANN predictions on the thermal properties of TiO2-Ag hybrid nanofluids: Consideration of temperature, particle loading, ultrasonication and storage time

The TiO2-Ag hybrid nanofluids were prepared by diluting high-concentration nanofluids and adding Span80 as surfactants. The stability of nanofluids was studied by taking photos of the nanofluids with storage time of 0–30 days. The thermal conductivity and dynamic viscosity were measured at different volume fraction, temperature and ultrasonication time. The results showed that compared with the base fluid, the maximum enhancement of thermal conductivity was 9.98%, and the maximum dynamic viscosity ratio was 2.78. And ultrasonication treatment is recommended to alleviate the sedimentation of nanofluids. Then, two artificial neural networks (ANNs) were established and the size of the networks was optimized according to the relative error to improve the ability to predict the thermal properties of nanofluids. The results show that the maximum relative error of the prediction of thermal conductivity and dynamic viscosity is 1.44% and 3.54%, respectively, which is beneficial to saving experiment time and cost.

Efficacy evaluation of oxide-MWCNT water hybrid nanofluids: An experimental and artificial neural network approach

The temperature dependencies of the thermophysical properties of different hybrid nanofluids have been investigated in the present work. Laboratory experiments were performed and optimized ANN model was developed for prediction and regression analysis. MWCNT-water based Al2O3, TiO2, ZnO and CeO2 nanofluids were used for this purpose. Metal oxide based nanofluids and MWCNT nanofluids were prepared and mixed in the 80:20 volumetric ratio. Nanofluids were prepared for volumetric concentrations varying from 0.25% to 2.0%. Thermophysical properties of hybrid nanofluids were measured at temperatures varying from 25 °C to 50 °C. Thermal conductivity ratios, specific heat, dynamic viscosity ratio and density were obtained against varying parameters. The CeO2 - MWCNT/water hybrid nanofluid showed highest efficacy with excellent thermophysical properties and highest Mouromtseff number (MO). A hyper-parameter optimized ANN model predicted the properties of hybrid nanofluids across four thermophysical parameters. The ANN predicted results provide good accuracy with experimental results (R > 0.999, MSE < 0.001, Deviations < ± 5%).

Study of physical-chemical and rheological properties of high-paraffin oils

The temperature dependence of physical-chemical and biological properties of high-paraffin oil was studied in laboratory conditions. The experiments were carried out on the oil samples without agents and with addition of 800 g/t composition developed at the ratio of Difron-4201 + Difron-3705 = 1:1. The increase in the density for 3.8 %, in the ratio of surface tension for 16 %, in the ratio of kinematic and dynamic viscosity up to 88 %, as well as in the ratio of the thermal expansion for 50.11 % was observed in the samples without agents in the temperature rise to 50K. In the samples included in the composition, the surface tension, kinematic and dynamic viscosity sharply decresed in all temperature fields compared to the samples without agents, the density practically did not change, and the ratio of thermal expansion volume slightly differed in all temperature fields.

Development of an artificial neural network for the prediction of relative viscosity of ethylene glycol based nanofluids

In this paper, we have developed an artificial neural network (ANN) model for the prediction of the viscosity of ethylene glycol-based nanofluids using data available in the literature. To develop the model, 377 data points were taken from the available literature. The data includes MgO, $${\hbox{Y}}_{{3}}{\hbox{Al}}_{{5}}{\hbox{O}}_{{12}}$$ , $${\hbox{In}}_{{2}}{\hbox{O}}_{{3}}$$ , Ag, $${\hbox{SiO}}_{{2}}$$ , Fe, Mg(OH) $$_{2}$$ , ZnO, SiC, $${\hbox{Al}}_{{2}}{\hbox{O}}_{{3}}$$ , $${\hbox{CeO}}_{{2}}$$ and $${\hbox{Ce}}_{{3}}{\hbox{O}}_{{4}}$$ nanoparticles. The inputs given to the ANN model were the diameter of the nanoparticles, temperature, and concentration of the nanoparticles, whereas output was the ratio of dynamic viscosity of the nanofluids to that of the base fluid. The ANN model was trained using 80% of the dataset and the rest of the dataset was used for testing the performance of the developed model. In order to prevent the model from getting overfit, dropout layers were also used. The trial and error method was used to find the optimum model. The optimum model consisted of 2 hidden layers and 45 neurons in both the hidden layers. The developed model shows good performance with the value of mean square error for the training data and test data being 3.9E−04 and 4.4E−04, respectively. The value of correlation coefficient (R) for the training data and test data was found to be 0.9962 and 0.996, respectively. Despite the high number of neurons in hidden layers, performance parameters reveal that there is no overfitting in the model. A comparison between the experimental values and the values predicted by the ANN model is also done in this paper.

Prediction of nanofluid viscosity using multilayer perceptron and Gaussian process regression

More than a decade, a numerous experimental and theoretical studies of thermophysical properties of nanofluids are conducted to reveal its heat transfer characteristics. Due to nanofluid unique thermal properties, it is broadly used in various applications from automobile applications to biomedical applications. Despite that various experimental and theoretical studies of nanofluids are developed, the accordance between them is very little and also it is tiresome and expensive. To predict the thermal properties in an easy way, soft computing tools are utilized. In this research work, dynamic viscosity ratio of Al2O3/H2O is predicted using machine learning techniques like multilayer perceptron and Gaussian process regression. In the proposed multilayer perceptron—artificial neural network model, varying a range of neurons in the hidden layer and using Levenberg–Marquardt as training function, it is found that 6 neurons in the hidden layer give less root mean square error value of 0.01118. Different kernel functions are opted to train the proposed Gaussian process regression model, and it is found that Matern kernel function shows the best performance with less root mean square error value of 0.018, and regression coefficient value of both the models is 0.99. This research work will reduce the experimental test run cost, and the models are accurate in prediction.

Regression analysis for thermal properties of Al2O3/H2O nanofluid using machine learning techniques

Nanofluids possess higher thermal properties than the other conventional base fluids. Many investigators suggested that the nanofluids have the potential to apply in various engineering fields. In real time situation it is challenging to determine the thermal conductivity of nanofluids with accuracy as they have many depending factors. Moreover, numerous experimental tests are required to acquire the thermal conductivity of nanofluids accurately. In this research paper, thermal conductivity ratio and dynamic viscosity ratio of Al2O3/H2O nanofluid are predicted accurately by using Gaussian Process Regression (GPR) methods. The input predictor variables used in this model are temperature, volume fraction and size of the nanoparticles. 222 experimental data sets are taken to predict the thermal conductivity ratio (TCR), dynamic viscosity ratio (DVR) and also the effectiveness of the predictor variables in predicting the response variables are extensively studied and found that the temperature is the crucial factor to enhance the thermal conductivity ratio. The proposed modeling is performed by using MATLAB software. The predictions were evaluated by various evaluation criterions. It is observed that an optimized Gaussian process regression (GPR) method with matern kernel function shows an accurate agreement with experimental data with Root Mean Square Error (RMSE) value of 0.000126 for TCR and squared exponential kernel function show good agreement with experimental data with Root Mean Square Error (RMSE) value of 0.000045 for DVR. Regression coefficient value (R2) is 0.99; nearer to one hence the predicted results are reliable.

The Effect of Physical Properties of Fluids on the Process of Purifying the Main Gas Pipeline from Liquid Pollutants

The article deals with modern technical methods of improving the efficiency of gas pipelines cleaning. The most effective method of improving the efficiency of a gas pipeline is its periodical cleaning with mechanical treating units. In practice, a large number of cleaning pistons of various technological designs are used. Regardless of the design, none of them can completely remove the fluid accumulations. The reason for the decrease in efficiency is the presence of fluid in the cavity of the pipeline. The fluid can be of two types – high-viscosity resinous deposits and low-viscosity liquid deposits. When moving, they perform the role of local resistance. The type of the main gas pipeline purification process is largely determined by the physical properties of the fluid which is being displaced. The authors specify the functional dependence of the velocity distribution in the pipe cross-section while displacing the Newtonian fluid, as well as the value of the initial pressure of the liquid phase on the cleaning piston. The interaction of a purifying device with fluid accumulations having different physical properties is investigated. The authors develop the algorithm of calculating the volume of the flows over a moving boundary into a back-piston space, in relation to their velocity. The dependence of the volume of fluid flows caused by hydraulic shock for Newtonian and non-Newtonian fluids is composed. Based on the calculations, the authors plot the graphical dependence of the correction coefficient on the ratio of dynamic viscosity to the degree of consistency, as well as the dependence of the total flow rate on the speed of movement of the cleaning unit. The formula for calculating the correction coefficient is obtained. The article presents the results of calculating the value of the correction coefficient which takes into account the rheological properties of the fluid. In relation to the properties and rheology of the non-Newtonian fluid, the authors determine the optimal velocity of a treating unit.

Two-liquid electroosmotic thrusters for micro propulsion applications

We investigate analytically the thruster performances and power consumption rates of a two-liquid electroosmotic thruster based on slit microchannels with hydrodynamic slip walls. The two electrolytes are considered to have different material properties and are arranged in the configuration of a core liquid layer surrounded by immiscible outer liquid layers with the outer layers in contact with the microchannel solid walls, thus forming electrical double layers at the solid-liquid interface. Interfacial potential jumps and surface charge densities are included to model the liquid-liquid interfacial double layers. Results reveal that, with the properties of both liquids being identical, nonzero liquid-liquid interfacial electrostatics only slightly increase the thrust but noticeably reduce the thruster efficiency and thrust-to-power ratio due to the enhanced Joule heating and viscous dissipation caused by the increased charge distributions and distorted velocity profiles. Moreover, the thrust and efficiency can be substantially increased as the dynamic viscosity ratio is decreased with the density ratio fixed at one, whereas the thrust, efficiency, and thrust-to-power ratio are all significantly enhanced by increasing the dynamic viscosity ratio when the kinematic viscosity ratio equals to one. The bulk electrolyte concentration/conductivity ratio is identified as a key parameter capable of simultaneously maximizing one or more thruster performances. While improving upon the performances of the single-liquid electroosmotic thruster previously reported, the two-liquid results and modeling presented herein may likely relax the limitations on the choice of electroosmotic propellants, increase the operational flexibility of electrokinetic thrusters, and be further applied in space or underwater micropropulsion applications.