Multiphase Flow Dynamics

It’s a very broad question! I will try to answer it from the particular case of the industry that I know a little more about, the oil industry, and rely on the generosity of readers to extract together, from this window of analysis, the elements that can be generalized to the entire landscape of Brazilian industry.

Nowadays, industry firmly establishes the use of fractured horizontals wells for exploiting oil and gas reservoirs. In 2016, hydraulically fractured horizontal wells accounted for 69% of all oil and natural gas wells drilled in the United States. This work investigates the transient well responses of a multi-fractured horizontal well producing an Unconventional Reservoir. The created individual fracture responses originate from an infinitive reservoir and are considered diffusion equation full-time rate responses. The analytical screening process is helpful for prognosis, diagnosis, and improved modeling of hydrocarbon production and drainage. Screening analyses can generate valuable information for fracture diagnosis in addition to a well and fracture production prognosis, mainly when limited input data are available. Multi-fractured horizontal well rate time and pressure time responses represent the solutions to a diffusion equation with varying boundary conditions and fracture options (i.e., various fracture orientations, various fracture lengths, etc.). The well response solutions are analytical and the model screens a horizontal well with multi-fractured productions. The transient model calculates individual fracture rates, productivity indexes, and equivalent wellbore radius. Individual fractures are acid or proppant. Each fracture to a well inflow includes choking pressure effects. This presentation studies the transient decline, emphasizing a horizontal well with fracture wellbore responses positioned in Unconventional Reservoirs. We want to find out the most optimal number of fracture stages and support management in quickly making fast decisions, mainly when most G&G and reservoir data are limited or unavailable for a complete reservoir flow simulation study. To optimize a horizontal well production rate, we investigate the most significant effect of a reservoir, fracture, and well on such wells’ productivity. Further, we use an analytical model that quickly assesses the impact of various well or reservoir properties on well performance. The model is three-dimensional, heterogeneous, and considers full-time rate–pressure time solutions. It assumes single-phase flow and fractures positioned on a horizontal well are transverse or longitudinal of varying types (uniform flux, infinite conductivity, finite conductivity). We use various constraints and multi-run sensitivity for the prognosis of multi-fractured horizontal well productivity and its diagnosis. For screening and optimization of a multi-fractured horizontal well, we use a fast and robust numerical algorithm. This paper investigates a horizontal well-fractured design and proposes the most optimal number of created transversal fractures economically valuable. A semi-analytical screening efficiently generates rate–pressure time monophase transient wellbore responses. Such wellbore responses complement finite differences multi-phase model solutions that handle heterogeneous and complex geometry but include numerical dispersion when solving partial derivatives with the algebraic equation. The study estimates hydrocarbon production profiles for various fractures, including the most optimal fracture number (fracture height, fracture half-length, fracture conductivity). Further, it provides a workflow for optimizing a fractured horizontal well production and drainage with the risk assessments in an Unconventional North Sea Reservoir.

In this paper, a numerical study on the stationary state for the multiphase flow of oil in a pipeline-riser system is presented. The developed model considers that the flow is one-dimensional and three-phase throughout the system. The liquid and gas phases are considered compressible. Furthermore, it is assumed that oil and water have the same speed and are homogenized. The flow pattern in the pipeline and riser is determined based on the local state variables and inclination angle. The characterization of fluids is done according to the black-oil model. The conservation equations were solved numerically using MATLAB software [1]. For a constant separator pressure as boundary condition, the pressures calculated by the model with the thermal effects were higher than those obtained by the isothermal model. The average difference between them was 2.3%. The deviations occurred due to the effect of temperature on the mass transfer, compressibility, expansion, and the thermophysical properties of the phases. The stationary analysis shows that the temperature has a secondary effect on the flow in offshore systems. However, deviations about the isothermal model must be taken into account in order to improve the reliability of numerical results and better production planning.

Flow control valves are essential to the oil industry through exploration and production phases. These valves must be capable of operating in offshore wells under an extremely high-pressure regime. In addition to contact with abrasive fluids, the flow occurs at high speed, which leads the equipment to suffer significant abrasive wear due to the high flow rates and pressure drops. This work aims to evaluate the flow through a drilling choke, using Computational Fluid Dynamics (CFD) open-source software, OpenFOAM. The flow was evaluated for five stages of the valve’s opening and flow conditions (25.0, 26.0, 28.0, 30.5, and 35.0 percent open). The results were compared with the experimental data obtained from a water test proceeded in the oil industry. It was found that good adherence between numerical and experimental results for pressure drop and the simulations provided an extensive understanding of pressure and velocity fields, allowing to predict the areas of cavitation on choke valves.

Quick closing valve (QCV) is a widely applied technique in laboratory multiphase flow studies. It can be used as a reliable calibration method to pick up the volumetric fraction of the phases on the vertical column when the steady state of multiphase vertical streams is established. In laboratory Three-Phase Flow studies, thousands of trials are performed. Hence, it is suitable to automate QCV systems for holdup measurement. The automation improves costs, standardizes, and minimizes spending time with tiring repetitive measurements. This work presents the methodology and design of an automated QCV for Holdup measurement system for three-phase flow: air, kerosene, and water. For this, direct column heights measurements are obtained by an optical sensor precisely moved up/down. Furthermore, two pressure sensors are used to measure the weight of the three-phase column. Merging the data with the Maximum Likelihood Estimation algorithm, the methodology and its uncertainties are presented. Data Fusion reduces uncertainties, making it possible to check inconsistencies and detect failures. Automated validation tests show that it is possible to accurately measure small columns of less than 1% of the total column.

In oil production, multiphase flow, composed of oil, gas, and water, is often found in the production system. The conventional method to measure the flow rates of multiphase flow is by measuring the flow of the individual phases after separation, which is a method commonly used in host platforms. However, there are several cases in which this approach is not feasible or practical, for example, in subsea systems, for the measurement of individual wells in a commingled system. In this context, multiphase flowmeters are usually employed. These meters can measure multiphase flow without phase separation and typically have a Venturi as the primary element. Although Venturi tubes are standardized by International Organization for Standardization (ISO) 5167-4:2003, the standard does not cover the Discharge Coefficient (Cd) for Multiphase Flow. Moreover, there is little academic work devoted to investigating the Discharge Coefficient of Venturis with Multiphase flow. In this work, numerical simulations were performed in Computational Fluid Dynamics based on the finite volume technique in three dimensions, using a non-homogeneous model (i.e., gas-liquid slip ratio \(\ne \)1), through the ANSYS Fluent software, for a Venturi meter in vertical and horizontal positions. Finally, the results are discussed and compared to other academic works.

Research devoted to understanding, modeling, and engineering multiphase flows have been the aims of the Industrial Multiphase Flow Laboratory (LEMI), located in the countryside of the state of São Paulo for nearly two decades now. The accurate determination of the spatial distribution of the phases in multicomponent and turbulent flows in big pipes using a homemade wire-mesh tomographic system, through which the phase fraction and the flow pattern involved can be obtained, the synchronized use of state-of-the-art equipment (PIV, wire-mesh sensor, and high-speed video camera) for the detailed study of turbulence in annular ducts, and the application of collimated gamma-ray densitometry for measurement of interfacial geometrical properties of stratified flows are among the achievements of the LEMI’s team that are described in the paper. In addition, full-scale experiments and recent developments in which data-driven and physics-informed machine learning techniques were used to predict two-phase flow parameters are discussed. The use of artificial intelligence is a new trend in our field of investigation and the results, although promising, indicate that physics is still necessary as big data are not available in many important engineering applications.

Flow measurement is an essential task to production management, well monitoring, custody transfer, and legislation matters for natural gas production plants. Differential pressure (DP) meters are an economically attractive and reliable alternative for gas flow measurements. On the other hand, wet gas flows occur due to the nature of processes, especially at upstream gas production. Although the performance of DP meters in single-phase flows measurement is well known and consolidated in the literature, for wet gas applications, the wetness produces a positive bias in the differential pressure, called over-reading, inducing an erroneous gas flow rate reading, if not corrected. Motivated to know and manage such over-reading, several authors have investigated this phenomenon, proposing empirical correlations to correct flow readings. In this work, the most relevant correlations are investigated, comparing their performance and limits of each one.

Electrical impedance tomography is being widely applied to multiphase flow investigation in techniques such as void fraction and dispersed phase flow velocity measurements. The technique is desirable since it presents no ionizing radiation, has a high time resolution, and is relatively low cost. The system works by injecting bidirectional electrical currents into the domain. It is necessary to measure effectively the outcome of the injection, which is commonly a sinusoidal excitation. It is crucial to demodulate this voltage effectively to allow a good accuracy and speed of the system. A way to do this demodulation is by applying a digital phase-sensitive detector, which can divide the signal into amplitude and phase information. It is necessary to multiply a sine and cosine reference to retrieve the signal information, using the Coordinate Rotation Digital Computer (CORDIC) algorithm in this work, to the digitized signal. For that matter, the objective is to implement a digital demodulation procedure utilizing a phase-sensitive detector, generating the reference signals by the CORDIC algorithm using an open-source microcontroller prototyping board, such as the Arduino Due. The accuracy and the noise are investigated further by measuring a reference signal.

Multiphase flow measurements allow monitoring and control of flows in real time. The extraction of oil in new fields has resulted in the demand for technologies capable of acting in extreme conditions, such as the high conductivity of saline water. Conductivity variation can impact EIT image reconstruction, and an alternative to ensure image reconstruction is to make online calibration viable. To support online calibration solutions, the study of the impact of conductivity on performance criteria can contribute to safety and control. Therefore, this article aims to assess the behavior of EIT performance criteria according to variations in conductivity, through the analysis of the conductivity effects on measurement errors, through the most common indexes for the analysis of measurement errors, for example, signal-to-noise ratio (SNR), and reciprocity error (RE). Through this study, it is possible to observe that in low concentrations, it is necessary to increase the signal conditioning gain according to the behavior of the solution conductivity. After a specific concentration, the conductivity stabilizes, and there is no need to adjust the gain.

The two-phase flow pattern prediction in pipes is a crucial design factor for the energy industry, given its influence on the system’s pressure drop and hold-up. A common approach is to use phenomenological models to predict those parameters as a function of the two-phase flow pattern. As more experimental data became available in the literature, the machine learning methodologies also became an option. In this work, we evaluate the use of data-driven machine learning to predict the liquid-liquid flow pattern transition. The database comprises data from the open literature. Although there is not the same amount of liquid-liquid flow data available, unlike for gas-liquid flow, this study shows that it is possible to predict the liquid-liquid flow patterns using the data-driven approach regardless of the viscosity ratio. Dimensionless parameters derived from the two-phase flow’s governing equations are used to train XGBoost. Four main groups of flow patterns were used in this work: stratified, intermittent, annular, and dispersed. The algorithm’s hyperparameters are tuned using cross-validation and accuracy as the target metric. In addition, a per-flow-pattern-map accuracy is also shown.

Developing new engineering technologies relies on the understanding of complex multiphase flows with heat and mass transfer. Such flows involve two- and four-way interactions between particles/droplets and the continuous career phase in both laminar and turbulent spectrums. This paper provides an overview of these flows in a number of engineering applications including (i) spray flows in diesel and gas turbines, (ii) biomass pyrolysis, and (iii) nanofluid microchannels. The methods addressing such multiphase flows are classified into two main groups including Eulerian–Eulerian and Lagrangian–Eulerian methods. Eulerian–Eulerian methods treat the particle/droplet phase as a continuous phase along with the carrier phase. Lagrangian–Eulerian techniques track individual particles and droplets while treating the fluid phase surrounding the particles/droplet as a continuum. Eulerian–Eulerian models are more common when the particle/droplet mass loading is high such as biomass pyrolysis that can be modelled in the concept of the Granular flows while Eulerian–Lagrangian methods are more suitable for the secondary breakup and dilute spray regions. For nanofluid applications with low mass loading (<5%), it is also common to use mixture models that solve one set of equations for the mixture, while the properties such as density and viscosity are computed for the mixture. If the flow is turbulent, as presented in spray flows, models are required to address the effect of turbulence. Both large eddy simulation (LES) and Reynold averaged Navier–Stokes (RANS) frameworks have been widely adopted for modelling spray flows in internal combustion engines. The next requirement for such flows involves sub-models for different physical phenomena such as particle/droplet dispersion, breakup, phase change, heat transfer, and particle/particle interactions such as collision and agglomeration.

Flow patterns are found in many processes involving multiphase flows in the industry. This experimental investigation focuses on the behavior of the vorticity fields found in the liquid-vapor interface during flow boiling of R-600a with heat flux varying from 5 to 20 kW/m\({}^{2\ }\) and fixed mass flux of 890 kg/(m\({}^{2}\)s) at a saturation temperature of 17 \(\mathrm {{}^\circ }\)C. Tests were performed in a horizontal tube with 1.0 mm ID. Four different flow patterns were identified based on images, and the vorticity fields were investigated using an optical flow method.

Heat transfer and pressure drop during convective boiling and condensation are intimately related to the behavior of the liquid-film thickness along the tube perimeter. In this context, the present paper provides liquid-film thickness measurements at the top of the conduit during in-tube convective condensation inside a horizontal channel of 9.43 mm internal diameter. Experiments are performed for R290 at mass velocities ranging from 50 to 250 kg/m\({}^{2}\)s, vapor qualities from 0 to unity, and heat fluxes from 5 to 60 kW/m\({}^{2}\). In general, a negligible effect of heat flux was noticed. Also, the behavior of the liquid-film thickness with increasing quality varies according to the mass velocity due to flow pattern changes.

In this study, a model of the total thermal resistance of a polymeric pulsating heat pipe was developed and compared with experimental results. Two configurations were tested, the first one with 2.0 mm internal diameter with one single turn in the adiabatic section in vertical favorable \((+90^{\circ })\), the second with 1.6 mm(I.D.) 80 turns in the adiabatic section in vertical unfavorable \((-90^{\circ })\). R134a was used as working fluid, and the filling ratio was equal to 60%. From the proposed, it can be concluded that the mean absolute error for total thermal resistance is in the range of 24–30%.

The studies carried out in the area of cell preservation have been of significant importance in recent years. This process, known as cryopreservation, has been used for decades and aims to preserve various cellular materials at cryogenic temperatures. Different methods allow cryopreservation, where the best known are the slow freezing and vitrification processes. Regardless of the process, it is necessary to use cryoprotective agents (CPAs) in conjunction with the cells to avoid possible cell damage during cryopreservation. Regarding the methods, they differ in their cooling rates and the concentration of CPAs used. According to some studies, the method that has been most studied is that of vitrification, which seeks to increase the cooling rate, reaching values above 20,000 \(^\circ \)C/min. Evaporation by a thin film of liquid nitrogen is one of the methods of vitrification, which uses a microstructure with a finned or porous surface for evaporation, and in these conditions cooling rates of up to 150,000 \(^\circ \)C/min were found, which shows a significant advance and alternative for cell cryopreservation.

Multiphase flows with viscoplastic materials are of paramount importance in many fields of science, being directly related to extremely important biomedical, environmental, and industrial situations. In the present work, two major multiphase flow scenarios involving viscoplastic materials are investigated: (1) the viscoplastic dripping; and (2) the bubble rising in a viscoplastic medium. In the former, we explore the breakup dynamics of a viscoplastic filament stretched by both gravity and surface tension. In the latter, we focus on the plastic effects that prevent an air bubble from moving via buoyancy in a viscoplastic medium. These problems are analysed by performing two-dimensional numerical simulations based on an adaptive variational multi-scale method for two materials (viscoplastic medium/air). The remarkable ability of the numerical framework in capturing complex multiphase systems with free surfaces is underlined by depicting the referred flow cases in the light of energy budget analyses, and scaling laws, thanks to which their physical mechanisms are stressed.

It is well known that the 4-equation formulation of the two-fluid model is ill-posed. As a result, it is impossible to differentiate between the errors originating from uncertainty in the empirical closure models and the nonphysical oscillations due to ill-posedness of the equations. The present work uses a 5-equation formulation, by adding a volume fraction evolution equation, which is unconditionally hyperbolic. To solve the resulting system of equations, a high-resolution Roe’s scheme is developed, and to keep the solution time practical, an adaptive mesh refinement algorithm is implemented. To obtain the wall shear stresses, a novel set of analytically developed friction equations is used for the non-Newtonian liquid phase. Finally, the capability of the developed code has been examined for the terrain slugging cases.

The present study simulated the dynamic behavior of the water–air interface in a cylindrical tank stirred mechanically. CFD techniques were applied using the software ANSYS-Fluent. The Volume of Fluid (VOF) model with explicit formulation coupled to the \(\upkappa \)-\(\upomega \) SST turbulence model was employed to numerically represent the transient displacement of the water–air interface starting from a situation of stagnated flow. An isothermal operation was considered for the case studied. A simple experimental apparatus composed of a glass vessel filled with dyed water and a mechanical stirrer with a pitched-bladed impeller was used to generate the experimental data of the interface position along the time. The model accuracy was evaluated at stirring rates of 300 and 400 RPM. According to the results, the geometric shape profile of the vortex at the pseudo-stationary state could be reasonably well reproduced by the model. However, the model could not generate accurate results regarding the transient behavior of the vortex formation. Additional strategies should be tested to enhance the model capability to reproduce the transient displacement of the water–air interface due to the rotational flow.

In the context of research on turbulent multiphase flows, the experimental and numerical reports available in the literature on downward bubble columns are still relatively scarce. Substantial advances in multiphase models, turbulence models, and new constitutive proposals for interfacial forces prove that the line of research is active and requires more scientific investigation. In this line, the current work aims to carry out a preliminary numerical analysis of a downward bubble column in a vertical tube with the ANSYS Fluent commercial package. A vertical pipe comprises the geometry used in the numerical experiment with a 20mm inner diameter. The multiphase flow is characterized by two average bubble diameters, 1.75 and 2.2 mm, and a gas volume fraction ranging from 2 to 10\(\%\) at the inlet. Regarding the analysis, initially, the convective intensity was varied to establish its influence on the axial velocity profile of the continuous phase and the void fraction distribution in the radial direction. At last, the gas flow rate was gradually increased to observe its effects on the radial void distribution. The results achieved were validated by comparison with well-established experimental data and presented satisfactory agreement in general.

In this paper, integrating different cooling techniques into a microchannel heat sink (MCHS) is evaluated to enhance the heat transfer rate. A parametric study is conducted using the computational fluid dynamics simulation consisting of the discrete phase model (CFD-DPM) to understand the effect of operational and geometrical parameters on cooling performance. The CFD-DPM simulations for varying different influential parameters are conducted to obtain the local temperature over the silicon wafer wall, creating a large set of samples. The artificial neural network (ANN) method is then employed to discover an accurate model to predict the local temperature. The ANN model includes two hidden layers and 24 neurons in each layer, showing a precise estimation of temperature with an overall mean square error (MSE) value and correlation coefficient (R) of 6.974810\({}^{-7}\) and 0.9952, respectively. The temperature distributions along the silicon wall predicted by both CFD-DPM and ANN models verify that smaller sizes of alumina nanoparticles improve heat transfer remarkably compared to larger particles.

Over the years, the multiphase flow has been playing an essential role in many industry sectors. However, prediction of flow pattern and pressure drop with accuracy is still challenging. For this reason, this paper presents a bibliographic review of mechanistic models applied to multiphase flow. Then, flow pattern and friction loss models were selected to be validated and applied to an experimental circuit in the Research Group for Oil and Gas Flow and Measurement (abbreviated as NEMOG, in Portuguese), considering its operational capacity. Furthermore, operational limits could be estimated for multiphase flow.

This study aims to show some aspects of flow similarity among an actual extraction plant of oil production and the design of a lab flow circuit. Emulsions are formed when oil and water are pumped from a reservoir to a separator vessel in oil production. In Brazil, oil production is mainly offshore and presents kilometric dimensions. In order to design a laboratory-scale flow circuit while maintaining some dynamic resemblance to the production lines, technical challenges must be faced, such as the balance among the increase in pressure drop as a consequence of the decrease in tube diameter due to the geometric similarity. Even so, the Weber number fits flow similarity requirements.

Gas hydrates formation and agglomeration represent a significant challenge in flow assurance during oil and gas production operations. An alternative to managing this problem is the use of anti-agglomerants (AAs), allowing hydrates to flow as solid particles dispersed in the liquid phase. Although the particles are henceforward not susceptible to agglomeration, it is still essential to understand how those particles affect and are affected by the gas-liquid multiphase flow structures. This study evaluates the influence of the introduction of particles, with properties similar to gas hydrates, into the multiphase flow, focusing on the slug flow pattern. The experiments were conducted in a 9-m length, 26-mm ID flow loop, with air and water at ambient conditions as working fluids. The particles were made of polyethylene with a density of 937 kg/m\(^{3}\), similar to gas hydrates. The particle sizes tested were 100 \(\upmu \)m, 200 \(\upmu \)m, 300 \(\upmu \)m, and 400 \(\upmu \)m, with volumetric concentrations of 1%, 2.5%, and 5%. This study discusses how the particles influence the velocities and lengths of the structures and how the multiphase flow affects the transportability of the particles.

Slug flow is present in many industrial processes, including the ones related to the petroleum industry. Such flow pattern is characterized by the intermittent repetition of liquid slugs that may or may not be aerated and elongated bubbles that flow atop a liquid film. Most of the existing models for slug flow have been developed for two-phase water-air flows, but in oil and gas production, the liquid phase can be substantially more viscous than water. This article aims to evaluate the effect of liquid viscosity increase on slug flow parameters, such as bubble velocity and frequency. An experimental study on liquid-gas flows in a 26 mm ID and the 8.65 m long horizontal pipe was developed to achieve this goal. Water and mixtures of water and glycerin with a viscosity of 5.46, 10.27, 15.39, 20.33, and 30.37 cP comprise the working liquids. The slug flow parameters were measured by a resistivity sensor located at one measuring station. Results show that the increase in the viscosity of the liquid results in an increase in the velocity of the elongated bubble. The effects on the slug frequency depend on the superficial velocities of the fluids.

The intermittent transit of gas and liquid pockets in a pipe is the most distinctive characteristic of the gas–liquid two-phase slug flow pattern. This flow regime is found mainly in oil and gas production and transportation lines. In deep-water oil operations, the pipes must conform to the seafloor, thus causing direction changes in the flow. In this context, the present work presents an experimental and numerical study on gas–liquid two-phase slug flows in ducts with slight direction changes. The pipeline consisted of a horizontal stretch followed by a downward inclined one with −3\(^{\circ }\) and −5\(^{\circ }\) concerning the horizontal in a 26-mm ID, 35.6-m long pipe. Along the experimental circuit, the phases are detected by employing resistive sensors installed in four measuring stations that monitor the characteristic of slug flow parameters, namely the elongated bubble velocity and the unit cell frequency. In the numerical part of this study, a transient methodology based on a simplified two-fluid Lagrangian model was used. In addition, this methodology simulates the gas–liquid regime transitions in pipes with a direction change from horizontal to downward inclined flow. Both the complete and the partial slug dissipations were observed in the downward section. The mean values of the slug flow parameters and the stratification process found both experimentally and numerically presented a good agreement.

Granular materials are solid particles whose collective dynamics produce unique phenomena. They can be uncounted for in industrial applications as dry or wet bulk materials. The most straightforward systems, in dry configuration, can be modeled as granular crystals formed by orderly arrangements of particles without significant relative movement. Possible applications of granular crystals are devices to control wave propagation. Proposals to attenuate impacts and filter mechanical waves are discussed. For particles with more energy and degrees of freedom, with cohesive forces, as van der Waals forces and capillary forces, in the case of wet granular material, a more general 3D modeling is needed. Granular flow is critical in the mining industry, where industrial steps process can be optimized. The different forms of numerical simulation of granular flows are presented in this chapter. A review of some investigations from the authors is briefly discussed. In the general DEM method, examples are presented for dry particles: granular crystal modeling and wet granular flow. For industrial mining cases, numerical and experimental results are provided for transfer chutes and hopper feedings cases studies. Modeling discussion, calibration steps, practical applications, and perspectives are presented.

During the fall of bulk materials, the air around the material mainstream is dragged by the non-slip condition modifying the near pressure and velocity fields generating air currents around the bulk material fall. A particle that comes off the mainstream will be subject to the drag force due to the moving air and can be transported away, characterizing the formation and dispersion of dust. This work applies a computational model in an iron ore conveyor belt transfer chute to evaluate the forces acting on microparticles that can be carried away from the control volume. The computational model is easy to implement, has low computational effort, and allows to map the particle’s path making it possible to estimate the particle diameters with a greater propensity for dust formation than observing the preferred dust escape paths. The capacity of an extractor fan to absorb suspended particles was also evaluated. Analytical solutions for the particle velocity in continuous medium considering the Stokes flow are presented and used in model validation. Physical parameters relevant to flows involving particle displacement (specifically iron ore particles) are presented and discussed: terminal velocity, terminal time, relative Reynolds number, drag coefficient, and suspension time.

This work aims to present a CFD Multiphase in order to calculate the induced airflow rate produced by a free-falling bulk material. The numerical solution is obtained through the DDPM model (Dense Discrete Phase Model) implemented in the ANSYS Fluent commercial code. This analysis tool will enable an improvement of dedusting projects in industries that work with granular materials. The simulations performed were compared with other computational methods and experiments and semi-empirical models available in the literature, obtaining good results.

The citizens of urban regions constantly suffer from dust particles present in the air that are dispersed mainly from the local industries’ facilities. To understand the dispersion of dust caused by the free fall of granular material, we have observed that the dust dispersion is made by forming a toroidal vortex. We studied a vertical vortex to carry out an analytical study of the velocity field formed by the vortex. Then by this study, it was possible to establish the velocity field of a toroidal vortex by the contribution of two vortices with different orientations.