Gas Viscosity Research Articles

Vortex breakdown in variable-density gaseous swirling jets

Theoretical predictions and numerical simulations are used to determine the transition to bubble and conical vortex breakdown in low-Mach-number laminar axisymmetric variable-density swirling jets. A critical value of the swirl number $S$ for the onset of the bubble ( $S^*_B$ ) and the cone ( $S^*_C$ ) is determined as the jet-to-ambient density ratio $\varLambda$ is varied, with the temperature dependence of the gas density and viscosity appropriate to that of air. The criterion of failure of the slender quasi-cylindrical approximation predicts $S^*_B$ that decreases with increasing values of $\varLambda$ for a jet in solid-body rotation emerging sharply into a quiescent atmosphere. In addition, a new criterion for the onset of conical breakdown is derived from divergence of the initial value of the radial spreading rate of the jet occurring at $S^*_C$ , found to be independent of $\varLambda$ , in an asymptotic analysis for small distances from the inlet plane. To maintain stable flow in the unsteady numerical simulations, an effective Reynolds number $Re_{eff}$ , defined employing the geometric mean of the viscosity in the jet and ambient atmosphere, is fixed at $Re_{eff}=200$ for all $\varLambda$ . Similar to the theoretical predictions, numerical calculations of $S^*_B$ decrease monotonically as $\varLambda$ is increased. The critical swirl numbers for the cone, $S^*_C$ , are found to depend strongly on viscous effects; for $\varLambda =1/5$ , the low jet Reynolds number (51) at $Re_{eff}=200$ delays the transition to the cone, while for $\varLambda =5$ at $Re_{eff}=200$ , the large increase in kinematic viscosity in the external fluid produces a similar trend, significantly increasing $S^*_C$ .

Shear stress tensor and specific shear viscosity of hot hadron gas in nuclear collisions

We extract the shear stress tensor of nuclear matter in the hadronic phase in high energy nuclear collisions. We use a blast-wave parametrization of the final state of nuclear collisions, including nonequilibrium deformations of particle distributions due to shear stress in the Navier-Stokes approximation. We fit spectra and elliptic flow of identified hadrons for a variety of collision energies and impact parameters at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). The systems analyzed cover a temperature range from about 110 to 150 MeV and vary in their chemical potentials for stable hadrons. We then attempt to estimate the specific shear viscosity $\ensuremath{\eta}/s$ of nuclear matter for various temperatures and chemical potentials in the hadronic phase. We assign systematic uncertainties to our results. Using a recent systematic study of fluid dynamics pseudodata with the same blast-wave model [Z. Yang and R. J. Fries, arXiv:2007.11777], we apply a correction to the raw fit results which removes some biases typical for blast-wave fits. This work is complementary to efforts using viscous fluid dynamics to extract the specific shear viscosity of quark gluon plasma at higher temperatures. We put our work in context with existing theoretical calculations of the specific shear viscosity.

A viscously dissipated Blasisus boundary layer flow with variable thermo-physical properties: An entropy generation study

This work presents the entropy generation of an incompressible boundary layer flow over a heated flat-plate with temperature dependent viscosity. The viscous dissipation effect is considered in energy equation. Liquid and gas type fluids are discussed for the boundary value problem. Thermo-physical properties are assumed to in momentum, energy and concentration equations. This study has received more interest in applied engineering due to its theoretical and numerical advantages. We investigate the solutions for thermo-physical characteristics of modified viscous model along with entropy generation. The similarity solution was firstly introduced by Blasisus, it is used for the current modified viscous fluid by converting the governing equations into ordinary differential equations. Shooting method is used to solve the ordinary differential equations. The effect of viscosity for gases show an increase behavior for the base flow profile but for liquids opposite nature is noticed. Thermal conductivity and mass diffusivity also increases the temperature and concentration profiles. For large Brinkman number and dimensionless concentration ratio variable the entropy generation increases. The results of the physical parameters on the base flow, temperature, concentration and entropy generation are discussed through figures and are presented in detail. The comparative results are determined for a limited case and good agreement is analyzed with previously published article.

Weakly nonlinear propagation of focused ultrasound in bubbly liquids with a thermal effect: Derivation of two cases of Khokolov–Zabolotskaya–Kuznetsoz equations

A physico-mathematical model composed of a single equation that consistently describes nonlinear focused ultrasound, bubble oscillations, and temperature fluctuations is theoretically proposed for microbubble-enhanced medical applications. The Khokhlov–Zabolotskaya–Kuznetsov (KZK) equation that has been widely used as a simplified model for nonlinear propagation of focused ultrasound in pure liquid is extended to that in liquid containing many spherical microbubbles, by applying the method of multiple scales to the volumetric averaged basic equations for bubbly liquids. As a result, for two-dimensional and three-dimensional cases, KZK equations composed of the linear combination of nonlinear, dissipation, dispersion, and focusing terms are derived. Especially, the dissipation term depends on three factors, i.e., interfacial liquid viscosity, liquid compressibility, and thermal conductivity of gas inside bubbles; the thermal conduction is evaluated by using four types of temperature gradient models. Finally, we numerically solve the derived KZK equation and show a moderate temperature rise appropriate to medical applications.

Linear stability analysis of a time-divergent slamming flow

When a liquid slams into a solid, the intermediate gas is squeezed out at a speed that diverges when approaching the moment of impact. Although there is mounting experimental evidence that instabilities form on the liquid interface during such an event, understanding of the nature of these instabilities is limited. This study therefore addresses the stability of a liquid–gas interface with surface tension, subject to a diverging flow in the gas phase, where the liquid and the gas phase are both represented as potential fluids. We perform a Kelvin–Helmholtz-type linear modal stability analysis of the surface to obtain an amplitude equation that is subsequently analysed in detail and applied to two cases of interest for impact problems, namely, the parallel impact of a wave onto a vertical wall, and the impact of a horizontal plate onto a liquid surface. In both cases we find that long wavelengths are stabilised considerably in comparison with what may be expected based upon classical knowledge of the stability of interfaces subject to a constant gas flow. In the former case, this leads to the prediction of a marginally stable wavelength that is completely absent in the classical analysis. For the latter we find much resemblance to the classical case, with the connotation that the instability is suppressed for smaller disk sizes. The study ends with a discussion of the influence of gas viscosity and gas compressibility on the respective stability diagrams.

Seismo-acoustic gliding: An experimental study

The gradual temporal shift of the spectral lines of harmonic seismic and/or acoustic tremor, known as spectral gliding, has been largely documented at different volcanoes worldwide. Despite the clear advantage of the experimental approach in providing direct observation of degassing processes and related elastic radiation, experimental studies on gliding tremor are lacking. Therefore, we investigated different episodes of gliding of acoustic and seismic tremor observed during analogue degassing experiments performed under different conditions of magma viscosity (10-1,000 Pa s), gas flux (5-180×10−3 l/s) and conduit surface roughness (fractal dimension of 2-2.99). Gliding experimental harmonic seismic and acoustic tremor was observed at high gas flux rates and viscosities, mostly associated with an increasing trend and often preceding a major burst. Decreasing secondary sets of harmonic spectral lines were observed in a few cases. Results suggest that gliding episodes are mostly related to the progressive volume variation of shallow interconnected gas pockets. Spectral analyses performed on acoustic signals provided the theoretical length of the resonator that was compared against the temporal evolution of the gas pockets, quantified from video analyses. The similarities between the observed degassing regime and churn-annular flow in high viscous fluids encourage further studies on churn dynamics in volcanic environments.

Modeling of gas viscosity at high pressure-high temperature conditions: Integrating radial basis function neural network with evolutionary algorithms

Increase in global natural gas production over the last 15 years has led to the use of new and untapped reservoirs including high pressure-high temperature ones in order to meet the consumer demands. As flow characteristics of gas in various environments such as porous media, wells, and pipelines are influenced by its viscosity, it is an important parameter for petroleum engineers. In this work, an immense gas viscosity dataset consisting of 3017 laboratory data points was used for properly implementing two smart techniques: radial basis function neural network with two training algorithms as well as multilayer perceptron neural network with four training algorithms. By using these techniques, various models with high accuracies were developed for viscosities estimation of gas mixture, pure methane, and pure nitrogen at high pressures (5000–25000 psia) and high temperatures (100–1880 °F). The radial basis function (RBF) neural network with ant colony optimization (ACO) (namely RBF-ACO model) is considered as the best model. Average absolute relative errors of the aforementioned model for estimating pure methane, pure nitrogen and gas mixture viscosities are 0.36 %, 0.49 %, and 1.76 %, respectively. RBF-ACO model provides better results comparing with other presented empirical models. Also, RBF neural network optimized by particle swarm optimization (PSO) shows a high error for estimating the viscosities of methane and gas mixture and RBF neural network optimized by genetic algorithm (GA) yields a high error for estimating the viscosity of gas mixture. Afterwards, effects of input parameters on the viscosity value obtained by RBF-ACO model, were investigated using the relevancy factor. Finally, based on numerical simulation, a sensitivity analysis was conducted for measuring the uncertainty of cumulative gas production resulted from gas viscosity estimation for a high pressure-high temperature gas reservoir. This process indicates that accurate estimation of gas viscosity plays an important role in reliable estimation of cumulative gas production.

Equilibria and oscillations in a reversible mechanical system

The method of stochastic molecular modeling, developed by the authors for calculating the transport coefficients of rarefied gas in a free medium, is generalized to describe transport processes in confined conditions. The phase trajectories of the studied molecular system are simulated stochastically, and the simulation of the dynamics of the molecule is split into processes. First, its shift in the configuration space is realized, and then a possible collision with other molecules is played out. The calculation of all observables, in particular, the transport coefficients is carried out by averaging over an ensemble of independent phase trajectories. The interaction of gas molecules with the boundary is described by mirror or mirror-diffuse laws. The efficiency of the algorithm is demonstrated by calculating the selfdiffusion coefficient of argon in the nanochannel. The accuracy of modeling is investigated, its dependence on the number of particles and phase trajectories used for averaging. The viscosity of rarefied gases in the nanochannel has been systematically studied. It is shown that it is non-isotropic, and its difference along and across the channel is determined by the interaction of gas molecules with the channel walls. By changing the material of the walls, it is possible to significantly change the viscosity of the gas, and it can be several times greater than in volume, or less. The indicated anisotropy of viscosity is recorded not only in nano-, but also in microchannels.

Comparative performance analysis between conventional and square cyclones for solid Particle-Gas Separation: A review

Conventional cylindrical-body cyclone separators have been in use in the industry for a long time due to their many benefits, including simple design and construction, low running costs, no moving parts, and significant particle collection efficiency. Many studies have been done on this cyclone type because of its utility in areas like mining and agriculture. A cyclone with a square body, rather than a cylindrical one, was introduced in the previous three decades. Square cyclones are not well-known in the industrial world yet. Still, they have several advantages over conventional cyclones, including faster construction, quicker integration with boilers, and improved thermal efficiency when used with fluidized bed circulation-type boilers. This research compares the performance of square and conventional cyclones in terms of collecting efficiency and pressure drop. Factors including solid loading ratio, gas entry velocity, gas viscosity, and cyclone shape affect pressure drop and separation efficiency. According to data from published papers, conventional cyclones outperform square cyclones in terms of collection efficiency. However, simulation studies have shown that the pressure drop in a square cyclone is less than that in a cylindrical cyclone. Given that square cyclones are more straightforward to fabricate than conventional cyclones, the findings of this paper open up a lot of room for more research into developing square cyclones that can equal the performance of conventional cyclones.

In situ fluid and injection gas compatibility of huff-n-puff gas EOR in a low-permeability shale-sand-carbonate reservoir

A sufficient number of choices are available when it comes to injection gas for enhanced oil recovery (EOR) application in unconventional reservoirs, such as CO 2 and field gas to name a few. Most likely, these gases have various degrees of compatibility with the in situ reservoir fluid from the oil recovery increase standpoint. In some cases, they might not even be compatible at all with each other. Instead of creating a better oil extraction, the introduction of the gases could diminish the oil recovery. It has been observed that some gases have exceptional ability in increasing the oil production by decreasing the oil viscosity while moving towards completely vaporizing the oil phase as the gases’ molar fractions increase in the mixture. The optimum injection gas composition is the one that returns the lowest oil and gas viscosity while continuously vaporizes the oil phase at the same time. For instance, pure C 2 is the optimum injection gas composition for the in-situ reservoir fluid used in this study. The significant increase in oil recovery given by the optimum injection gas justifies such injection fluid composition optimization attempt proposed by this study. Furthermore, the injection fluid composition should be among the first to be optimized, before other operational parameters such as huff-n-puff cycle durations. • Some gas types increases the oil recovery of a particular unconventional reservoir better than other gas types. • A good injection gas choice not only lowers the oil viscosity, swells its volume, and vaporizes its heavy components. • A good injection gas choice should also shift the mixture P-T diagram favorably. • A good injection gas choice should therefore in theory be able to vaporize the reservoir oil completely.

Influence of ambient air viscosity on the accuracy of measurements of liquid properties in a levitating drop

In this paper, we consider low-amplitude capillary oscillations of a liquid droplet that has a spherical shape in equilibrium and is placed in an immobile light gas volume. In the approximation of low medium viscosity, and under the condition that the media differ greatly in density, a correction to natural frequency was determined and the viscous damping coefficient was estimated. Theoretical predictions were obtained analytically and verified by performing numerical calculations for water or mercury drops in the air. It is shown that the contributions of the viscosity and inertia of the gas to the real frequency of free oscillations of the system are insignificant. As regards the damping factor, the gas viscosity makes a contribution determined by the square root of its kinematic viscosity, which can no longer be neglected. The damping coefficient calculated relative to the liquid contribution linear in viscosity increases as the fourth root of the droplet size. For the water drop of 5 mm diameter, it is about ten percent, and for the mercury drop of the same size, the relative contribution reaches five percent. The results obtained are necessary for improving the "levitating" drop method, which is a variation of the dynamic capillary wave method used for non-contact measurement of viscosity coefficients and surface tension. A generalization of the Lamb formula for calculating liquid viscosity is proposed, which, in addition to the damping decrement of the quadrupole mode and the drop size, includes the density and viscosity of the gas, as well as the natural frequency of the system. The surface tension coefficient can be calculated using the Rayleigh formula, which, as it turns out, does not require a correction.

Comprehensive assessment and evaluation of correlations for gas-oil ratio, oil formation volume factor, gas viscosity, and gas density utilized in gas kick detection

For reliable gas kick detection modeling and simulation, the PVT properties of the gas must be predicted accurately. The property correlations available in open literature are developed mostly for certain regions and conditions, which usually over-predict or under-predict when applied to different regions and conditions. To assess these correlations and to determine their applicability and accuracy, a comprehensive evaluation is performed for 63 empirical correlations of four gas properties; gas-oil ratio GOR, oil formation volume factor OFVF, gas viscosity, and gas density based on published laboratory measurements. The GOR and OFVF correlations were evaluated on a regional basis and three best-fit correlations are recommended for each selected region including the Middle East, Central & South America, North America, Africa, and Asia. A universal new correlation for the GOR is developed in this study that can be used for any region in the world with better accuracy and wider range than all available correlations. Furthermore, based on the evaluation results, the most accurate correlations for gas viscosity and density at high-temperature and high-pressure (HTHP) conditions are recommended. The density-based models of the gas viscosity show close results within a minimum average absolute relative error (AARE) of 3.50% to a maximum of 4.45%. Further assessment for the equations of state based on real compositions of the gas kick is recommended for future work. The present work provides a comprehensive and one-stop source database for property correlations and measured data related to gas kick detection.

Second-generation dust in planetary systems: the case of HD 163296

ABSTRACT Observations indicate that large, dust-laden protoplanetary discs are common. Some features, like gaps, rings, and spirals, suggest they may host young planets, which can excite the orbits of nearby leftover planetesimals. Energetic collisions among these bodies can lead to the production of second-generation dust. Grains produced by collisions may have a dynamical behaviour different from that of first-generation, primordial dust out of which planetesimals and planets formed. We aim to study these differences for the HD 163296 system and determine whether dynamical signatures in the mixture of the two dust populations can help separate their contributions. We use three-dimensional (3D) hydrodynamic models to describe the gaseous disc with three, Saturn- to Jupiter-mass, embedded planets. Dust grains, of sizes $1\, \mu \mathrm{m}$–$1\, \mathrm{mm}$, are treated as Lagrangian particles with resolved thermodynamics and mass-loss. Initial disc and planet configurations are derived from observation-based work, which indicates low gas viscosity. The 3D approach also allows us to detect the formation of vortices induced by Rossby waves, where dust becomes concentrated and may contribute to planetesimal formation. We find that the main differences in the dynamical behaviour of first- and second-generation dust occur in the vertical distribution. The two populations have similar distributions around the disc mid-plane, although second-generation dust shows longer residence times close to the radial locations of the planets’ gas gaps. Sedimentation rates of $\mu$m-sized grains are comparable to or lower than the production rates by planetesimals’ collisions, making this population potentially observable. These outcomes can be extended to similar systems harbouring giant planets.

Application of Gene Expression Programming (GEP) in Modeling Hydrocarbon Recovery in WAG Injection Process

Water alternating gas (WAG) injection has been successfully applied as a tertiary recovery technique. Forecasting WAG flooding performance using fast and robust models is of great importance to attain a better understanding of the process, optimize the operational conditions, and avoid high-cost blind tests in laboratory or pilot scales. In this study, we introduce a novel correlation to determine the performance of the near-miscible WAG flooding in strongly water-wet sandstones. We conduct dimensional analysis with Buckingham’s π theorem technique to generate dimensionless numbers using eight key parameters. Seven dimensionless numbers are employed as the input variables of the desired correlation for predicting the recovery factor of a near-miscible WAG injection. A verified mathematical model is used to generate the required training and testing data for the development of the correlation using a gene expression programming (GEP) algorithm. The provided data points are then separated into two subsets: training (67%) to develop the model and testing (33%) to assess the models’ capability. Conducting error analysis, statistical measures and graphical illustrations are provided to assess the effectiveness of the introduced model. The statistical analysis shows that the developed GEP-based correlation can generate target data with high precision such that the training phase leads to R2 = 92.85% and MSE = 1.38 × 10−3 and R2 = 91.93% and MSE = 4.30 × 10−3 are attained for the testing phase. The relative importance of the input dimensionless groups is also determined. According to the sensitivity analysis, decreasing the oil–water capillary number results in a significant reduction in RF in all cycles. Increasing the magnitudes of oil to gas viscosity ratio and oil to water viscosity ratio lowers the RF of each cycle. It is found that oil to gas viscosity ratio has a higher impact on RF value compared to oil to water viscosity ratio due to a higher viscosity gap between the gas and oil phases. It is expected that the GEP, as a fast and reliable tool, will be useful to find vital variables including relative permeability in complex transport phenomena such as three-phase flow in porous media.

Modification of the Calculation Method for Dynamic Reserves in Tight Sandstone Gas Reservoirs.

The determination of dynamic reserves is important for tight sandstone gas reservoirs in production. Based on the geological and gas data of the Yan’an gas field, the influence of pressure on the properties of natural gas is studied by mathematical methods. At the same time, the modified flowing material balance equation is established considering the changes in gas viscosity and compressibility. The result shows that (1) the viscosity of natural gas increases rapidly with pressure; (2) the deviation factor decreases with pressure (P < 15 MPa) and then increases (P > 15 MPa) with temperature; (3) the compressibility decreases rapidly with pressure and increases with temperature; (4) compared with the results of the material balance method, the average error of the flowing material balance method is 33.95%, and the accuracy of the modified flowing material balance method is higher with an average error of 1.25%; and (5) a large change in the production will affect the accuracy of the modified flowing material balance method, especially a shut-in for a long time before the pressure drop production is calculated at a certain time, so data points that are relatively consistent should be selected as far as possible to calculate the dynamic reserves. The findings of this study can help in the accurate evaluation of dynamic reserves of the tight gas reservoir in the Yan’an gas field and are an important guide for the formulation of a rational plan for the gas reservoir and its economic and efficient development.

Applications of wireline formation testing (WFT) and downhole fluid analysis (DFA): Reviewing the importance of this technology in reservoir evaluation

Wireline formation testing (WFT) is an important aspect in both exploration and production phases for reservoir evaluation. WFT tools can directly measure the formation pore pressures and then the pressure profiles are used to identify the type of pore fluids, identify the fluids density, fluid contact estimation, depletion and overpressure quantification, detection of continuity and connectivity of the reservoir in both the lateral and vertical directions. WFT is mostly used to evaluate formation permeability and taking fluid sampling. The new generation wireline formation sampling tools include a downhole fluid analyzer (DFA), which can analyze the composition of fluids in real-time and under in-situ conditions and also can measure the spectra of crude oil. So, in result, it is possible to identify fluid compositional variation and reservoir vertical compartmentalization. The analysis of fluid composition depends on the optical absorption, and the mass fraction estimation for the three groups of hydrocarbons: methane (C1), C2-5, and C6 + along with CO2 as well. Also, it provides formation fluid properties like gas oil ratio (GOR), density, viscosity, and resistivity. The DFA results are subsequently validated and modified by laboratory analysis on the fluid samples attained from the formation. The potential advantage of early measurements demonstrates that the DFA is a good decision-making solution in early stage without waiting for the lab result for months. Also, early DFA measurements are important in completion designing and well testing, the establishment of fluid gradients in reservoirs and connectivity, identifying and validating fluid distributions and reservoir structures.

Research on optimal production distribution of tight sandstone gas reservoir

The determination of dynamic reserves is an important basis for rational production allocation. Based on the Yan’an Gas Field, the modified flowing material balance equation is established considering the changes of gas viscosity and compressibility. At the same time, a reasonable production allocation method for gas wells is developed. The result shows: ① μgCg decreases with pressure and increases with temperature. ② The error of the modified flowing material balance method is smaller compared with the flow material balance method, and the error is 1.25 %. ③ The great change of the production will affect the accuracy of the modified flow material balance method, especially the shut-in for a long time before the pressure drop production is calculated at a certain time, so the points with relatively constant should be selected as far as possible. ④ When the dynamic reserves are used for allocation, the initial decline rate decreases by 74.65 % on average, and the stable production period increases by 21.28 % and the stable production period increases by 1.79 % compared with the allocation method of open flow rate. ⑤ When there is a large error of dynamic reserves, it will lead to production deviation from the reasonable value. The findings of this study can help for the accurate evaluation of dynamic reserves and reasonable production allocation of tight gas wells in the Yan’an gas field, and is an important guide for the formulation of a rational plan for the gas reservoir and its economic and efficient development.

INVESTIGATION ON EFFECT OF SURFACE ROUGHNESS PATTERN TO DYNAMIC PERFORMANCE OF MEMS RESONATORS IN VARIOUS TYPES OF GASES AND GAS RAREFACTION

The average modified molecular gas lubrication (MMGL) equation, which is modified with pressure flow factors and effective viscosity, is utilized to analyze the squeeze film damping (SFD) on micro-beam resonators considering effect of surface roughness pattern in various types of gases and gas rarefaction. Then, effect of surface roughness pattern (film thickness ratio and Peklenik number) is discussed on the quality factor (Q-factor) of micro-beam resonators in various types of gases and gas rarefaction. Thus, effect of surface roughness pattern is significantly reduced as effective viscosity of gas decreases in higher mode of resonator and higher gas rarefaction.

Application of mathematical and machine learning models to predict differential pressure of autonomous downhole inflow control devices

Controlling reservoir fluid flow is important for maximizing petroleum production through wellbores. A major challenge that reduces the production of oil is early breakthrough of secondary fluids to the wellbore perforations. This occurs due to the low viscosity of gas and water relative to oil, and the heterogeneity of reservoir permeability. Autonomous inflow control devices represent a new self-regulating technology that helps to increase petroleum production, particularly oil, by restricting the production of unwanted fluids like gas and water into the wellbores. This study develops smart systems based on machine learning models to predict the performance of autonomous inflow control devices. Several machine learning models are evaluated including adaptive neuro fuzzy inference system, hybrid adaptive neuro-fuzzy inference system genetic algorithm, artificial neural network and support vector machine and their prediction performance is compared to that of linear regression, full quadratic regression model and the mathematical autonomous inflow control device performance model. Each model is developed to estimate the differential pressure of Equiflow autonomous inflow control devices based on ninety experimentally recorded data records. The range of equiflow autonomous inflow control device, viscosity, density and flow rate are the input variables and differential pressure is the output dependent variable of each model. The prediction accuracy of the models is assessed in terms of several standard statistical accuracy performance measures. These performance indicators confirm that the machine-learning models provide superior prediction accuracy for autonomous inflow control device differential pressure. Overall, the support vector machine achieves the most accurate predictions of all the models evaluated recording root mean square error of 0.14 Mpa and coefficient of determination of 0.98. On the other hand, the linear regression model records the lowest prediction performance, highlighting the non-linearity of the autonomous inflow control device processes. Cited as: Yavari, H., Khosravanian, R., Wood, D.A., Aadnoy, B.S. Application of mathematical and machine learning models to predict differential pressure of autonomous downhole inflow control devices. Advances in Geo-Energy Research, 2021, 5(4): 386-406, doi: 10.46690/ager.2021.04.05

Direct stochastic molecular modelling of transport processes in gases

The stochastic molecular modeling method (SMM) of transport processes in rarefied gases developed by the authors is systematically discussed in this paper. It is shown that, it is possible to simulate the transport coefficients of rarefied gas with high accuracy, using a relatively small number of molecules. The data of modeling the thermal conductivity coefficient are presented for the first time. The second part of the paper is devoted to the generalization of the SMM method for modeling transport processes in confined conditions. To describe the dynamics of molecules in this case, the splitting of their evolution by processes is used: first, the movement of molecules in the configuration space is simulated, and then their dynamics in the velocity space is imitated. Anisotropy of viscosity and thermal conductivity in nanochannels has been established. The interaction of gas molecules with walls is described by specular or specular-diffuse reflection laws. Gas viscosity can be either greater than in the bulk or less, depending on the law of gas interaction with the channel walls.