DescriptionThis study simulates well drilling and cuttings (sludge) transport using ANSYS Fluent. The wellbore is modeled as a cylindrical annulus containing a rotating inner cylinder (100 rpm). A non-Newtonian drilling fluid (CMC) flows through the cavity, entraining and lifting solid mud particles. An Eulerian multiphase framework is adopted: the primary phase is the CMC base fluid and the secondary phase comprises drilling solids.The Eulerian approach is suitable for high dispersed-phase loadings (>10%), slurry and liquid–solid transport, and deposition studies. Here, the base fluid volume fraction is 0.87 and the solids (drilling particles) volume fraction is 0.13. Viscosity behavior is non-Newtonian for the CMC phase (contrast to Newtonian fluids, whose shear stress varies linearly with strain rate).Geometry & MeshThe 3D domain consists of two eccentric coaxial cylinders, each 10 m long. The inner cylinder diameter is 0.128 m and the outer cylinder diameter is 0.444 m. Meshing is performed in ANSYS Meshing with an unstructured grid totaling 179,820 elements.Simulation SetupA pressure-based, transient (unsteady) solver is used. Gravity is included with a magnitude of −9.81 m/s². Because the well axis is inclined by 30° relative to gravity, the gravitational acceleration resolves to 4.9 m/s² in the xxx direction and 8.5 m/s² in the zzz direction. The inner cylinder’s rotation is prescribed at 100 rpm to promote solids lifting and separation within the annulus.Results & DiscussionPost-processing yields 2D and 3D contours of pressure, CMC velocity, drilling-solids velocity, CMC volume fraction, drilling-solids volume fraction, and turbulent kinetic energy. These fields characterize the coupling between rotation-induced shear and buoyancy components, illustrating how the non-Newtonian carrier mobilizes and transports the cuttings while mitigating deposition within the inclined wellbore.

This project investigates the pigging process in pipeline transportation using ANSYS Fluent. Pigging refers to the use of inspection devices, commonly known as pigs or scrapers, to perform maintenance and cleaning operations inside large-diameter pipes. In this simulation, the pig begins moving while the outlet valve remains closed, with the domain initially filled with air. The analysis focuses on the pressure distribution on the pig's surface and along the central plane of the pipe, with particular attention to the junction where two pipe sections meet, since this region is critical from a pressure standpoint.The geometry was created in SpaceClaim, and the mesh was generated in ANSYS Meshing using tetrahedral elements, chosen for their compatibility with the deformation and remeshing required by the pig's motion. The final mesh contains 659,988 volume cells and meets the quality requirements for the simulation.MethodologyThe motion of the pig through the pipeline is captured using the Dynamic Mesh method, with the Remeshing and Smoothing sub-models handling the deformation and regeneration of mesh elements as the device advances.ResultsThe simulation provides the static pressure distribution on the pig's surface, with clear variations visible from different viewpoints along the pipeline. An animation was also generated, illustrating the pig's continuous movement from the start of the simulation until it approaches the outlet.For pipelines containing fluids such as water or oil rather than air, the model can be adapted to represent these conditions, allowing the cleaning process to be evaluated under more realistic operating scenarios.

Sand Particle Sedimentation CFD Analysis, ANSYS Fluent TrainingIntroductionThis analysis presents a computational fluid dynamics (CFD) study of sedimentation behavior for three different sand particle sizes using ANSYS Fluent. The study examines how sand particles of varying sizes behave during sedimentation within a fluid medium, offering insight into settling patterns and particle distribution — information valuable for environmental engineering, sediment transport, and water treatment applications.The geometry was designed in ANSYS Design Modeler as a cylindrical domain, visible through the circular cross-section in the mesh. The domain was optimized to accurately capture particle sedimentation behavior under gravitational influence.ANSYS Meshing was used to generate a structured hexahedral mesh containing 388,797 elements, providing sufficient resolution to capture flow dynamics, turbulence effects, and particle distribution throughout the domain.MethodologyA pressure-based, steady-state solver was used to capture the equilibrium state of particle distribution within the fluid. The RNG k-epsilon turbulence model with standard wall functions was selected to represent the turbulent fluid-particle interaction occurring during sedimentation.The Eulerian multiphase model with implicit formulation was applied to simulate the interaction between the fluid phase and three distinct sand particle sizes — small, medium, and large. Gravitational effects were enabled throughout the simulation to accurately capture the sedimentation process.ResultsDensity contours reveal the distribution of the fluid-particle mixture across the domain, ranging from 998.20 kg/m³ to 1114.53 kg/m³, with higher densities concentrated near the bottom — reflecting particle accumulation due to sedimentation.Static pressure contours range from -80.92 Pa to 200.36 Pa, following a primarily vertical gradient with higher pressures near the domain's base, consistent with hydrostatic pressure distribution and the presence of settled particles.Volume fraction contours for each particle size reveal distinct settling behavior:Large particles (sand-l) reach a maximum volume fraction of 0.32, showing clear stratification and rapid settling concentrated near the bottom of the domain.Medium particles (sand-m) show a maximum volume fraction of 0.30, following a similar distribution pattern to the large particles but with a slightly more diffuse upper boundary.Small particles (sand-s) also reach a maximum volume fraction of 0.32, but remain far more uniformly distributed throughout the domain, indicating slower settling and greater suspension within the fluid.The water phase's volume fraction ranges from 0.37 to 1.00, complementing the particle distribution results.Vertical volume-fraction profiles at the outlet boundary further quantify this size-dependent behavior:Large particles show a sharp rise near the bottom, peaking at roughly 0.30.Medium particles exhibit a more gradual increase, peaking at approximately 0.28 near the bottom.Small particles maintain a much more uniform concentration throughout most of the domain height, peaking at only around 0.035.These results clearly illustrate size-dependent sedimentation behavior — larger particles settle rapidly and form distinct layers, while smaller particles remain largely suspended throughout the fluid. The findings offer practical insight into particle settling dynamics relevant to sediment transport and particle separation processes across a range of engineering applications.

Splitter Erosion CFD Simulation Training using DPM by ANSYS FluentDescriptionA splitter is a device used to uniformly distribute incoming fluid flow through outlets of matching shape and size. Beyond evenly dividing flow rate, splitters can incorporate filtration to remove impurities and improve outlet gas purity. Impurities such as sand and various metal oxides can cause progressive erosion on equipment surfaces over time, making erosion analysis on transmission pipelines and flow-distribution equipment a critical engineering concern.Using the Discrete Phase Model (DPM), this study examines how impurities within a working fluid affect erosion on a gas splitter body. The impurity-laden gas enters vertically at 5 m/s and is directed through three outlet nozzles. Impurity distribution, concentration, adsorption, and reflection behavior within the installed filters were analyzed using ANSYS Fluent, applying multiple erosion models to accurately predict erosion effects under varying operating conditions.The splitter geometry features three outlet nozzles, with a mainstream inlet diameter of 1.6 cm and outlet nozzle diameters of 0.3 cm. Filter fins measuring 2.5 cm in length are positioned inside the geometry, built using Design Modeler. The domain was meshed in ANSYS Meshing using an unstructured grid of 2,728,426 elements, with curvature and proximity refinement applied near the fins, and boundary layer meshing along the walls to satisfy turbulence model Y+ requirements.MethodologyThe governing equations were solved using ANSYS Fluent's pressure-based, steady-state solver, with gravitational effects excluded. Discrete phase particles were tracked using RANS with a Lagrangian reference frame, where particle inertia is balanced against the forces acting on each particle. Given the high-speed internal flow within the domain, natural gas density was treated as constant, with relevant thermodynamic properties — viscosity, thermal conductivity, and impurity density — defined accordingly.Key simulation parameters included:Natural gas properties: density of 0.65 kg/m³, viscosity of 0.00013 kg/m·sImpurity particles: density of 1600 kg/m³, uniform diameter of 0.15 mm, total flow rate of 0.04627 kg/sDPM settings: 10 continuous-phase iterations per DPM step, maximum step tracking of 50,000, trapezoidal tracking scheme, spherical drag law, and stochastic turbulent dispersion via the Discrete Random Walk modelParticle tracking outcome: of 24,900 tracked particles, 8,202 were trapped and 16,695 escapedBoundary conditions: 5 m/s velocity inlet, 0 Pa gauge pressure outlet, trap condition on fin walls, escape condition on external domain wallsTurbulence model: Realizable k-ε with enhanced wall treatmentSolution methods: SIMPLE pressure-velocity coupling, standard pressure discretization, second-order upwind for momentum, and first-order upwind for turbulent kinetic energy and dissipation rateFour erosion models were evaluated: the Generic model (broadly applicable, given sand is a common impurity across most cases), the Finnie model (empirically based, suited to malleable materials and sensitive to collision angle and velocity), the Oka model (accounts for wall hardness, making it well-suited to transmission pipe erosion analysis), and the McLaury model (intended for suspended solids in water, and found unsuitable for this particular case).AnalysisErosion contours across all applicable models consistently showed that particle impact on the upper wall — driven by high fluid velocity — produces greater erosion than other regions, with the outlet nozzle walls also experiencing elevated erosion. Oka erosion diagrams were monitored throughout the solution process to help assess convergence behavior.Impurity concentration contours revealed that near the splitter's outlet, high downstream velocity combined with a reduced cross-sectional area made particle exit difficult, leading to particle accumulation and increased impurity concentration in that region. However, the filter fins were shown to enhance impurity particle adsorption, as reflected in the trap-versus-escape particle tracking results.

Gas Particle Movement Through the Nozzle, CFD Simulation Tutorial by ANSYS FluentDescriptionThis simulation models gas-particle movement through a convergence-divergence nozzle using a two-way DPM model in ANSYS Fluent, with the nozzle operating under grossly overexpanded conditions.Convergence-divergence (also known as convergent-divergent or de Laval) nozzles are designed to accelerate flow from subsonic to supersonic speeds, with the narrowing throat section followed by a diverging outlet. When the exit pressure of such a nozzle is significantly lower than the surrounding ambient pressure, the flow is described as overexpanded — a condition that produces complex shock structures, flow separation, and pressure oscillations downstream of the throat. Understanding particle behavior under these conditions is particularly important in the gas and petrochemical industry, where nozzles of this type are widely used in gas transport, flow metering, and pressure-letdown applications, and where entrained solid or liquid particles can significantly affect equipment performance and erosion behavior.The 3D geometry was built using Design Modeler, and the domain was meshed in ANSYS Meshing with an unstructured grid totaling 16,245,216 cells.MethodologySeveral assumptions were applied to simulate this model: a pressure-based solver was used, only fluid behavior was examined (heat transfer was not simulated), and gravitational effects were ignored.Key simulation settings included:Viscous model: Realizable k-epsilon with scalable wall functionsPhases: air as the primary phase, gas particles as the discrete phase, using an explicit formulationBoundary conditions: velocity inlet at 5 m/s with an initial gauge pressure of 448,000 Pa and discrete phase escape condition; pressure outlet with 0 Pa supersonic gauge pressure and discrete phase escape condition; stationary wall with standard wall motionSolution methods: phase-coupled pressure-velocity coupling, PRESTO! for pressure discretization, and first-order upwind schemes for momentum, specific dissipation rate, and volume fractionInitialization: hybrid method, with a water velocity of 52 m/s in the y-direction and particle velocity initialized to 0 m/s in all directionsAnalysisThe results yield two-dimensional and three-dimensional contours of velocity, static enthalpy, and turbulence kinetic energy. The simulation illustrates how gas particles enter the nozzle from the inlet and travel through its convergent-divergent geometry, revealing how the nozzle's overexpanded shock structure and pressure distribution influence particle velocity under the given simulation conditions.

DescriptionThis project presents a numerical simulation of the ammonia flashing that occurs when liquid ammonia is injected through a small orifice nozzle. Flash boiling is a rapid evaporation process triggered by a sudden pressure drop, which leaves the liquid in an unstable state and drives a very fast phase change. Using the VOF multiphase model in ANSYS Fluent, the interaction between the liquid ammonia, its vapor, and the surrounding gas is resolved in time. The mass transfer between the liquid and vapor phases is the heart of the study: the simulation captures the jet breakup, the liquid-to-vapor phase transition, and the subsequent development of the two-phase ammonia flow within the domain.Geometry & MeshThe geometry was created in ANSYS SpaceClaim as a 2D symmetric domain. The lower horizontal line acts as a symmetry boundary, so only half of the physical domain is modeled to reduce computational cost. The geometry consists of an inlet nozzle section and a larger downstream chamber where the flashing and mixing take place, with the inlet and the two outlets clearly defined on the schematic to specify the boundary conditions. Meshing was performed in ANSYS Meshing, producing approximately 95,000 high-quality structured elements to ensure the numerical stability and accuracy of the simulation.MethodologyThe simulation employs a transient, incompressible, pressure-based solver to resolve the unsteady behavior of the flow field. The k-ω SST turbulence model is used to accurately capture boundary-layer separation and the unstable vortical structures in the ammonia jet. For the multiphase treatment, the VOF model tracks the interfaces between air, liquid ammonia, and ammonia vapor. Crucially, the Lee evaporation-condensation model is coupled with VOF to represent the mass transfer — the phase change from liquid ammonia to ammonia vapor — within the flashing region.ConclusionThe results show the injected liquid ammonia jet expanding into the larger chamber and rapidly converting into a two-phase mixture. The volume fraction contours clearly reveal the formation of a liquid film near the bottom wall, with the ammonia vapor fraction increasing downstream as the flashing and evaporation intensify. The velocity field shows a high-speed jet along the lower boundary and a large recirculation zone in the upper chamber, indicating strong mixing between the phases. The temperature contours confirm cooling in the liquid-rich region (around 270 K) and a warmer, vapor-dominated layer (approaching 300 K) — a direct consequence of the energy consumed during the phase change. Together, these results demonstrate how coupling the Lee model with VOF captures the mass transfer that governs ammonia flash boiling, providing a detailed picture of the evaporation-driven two-phase flow.

DescriptionThis project simulates combustion in a gas flare system using ANSYS Fluent, investigated through CFD analysis. The model was built in 3D using Design Modeler. Owing to the symmetrical structure of the flare and to reduce computational cost, only a 120-degree segment of the geometry was modeled.The flare has a cylindrical structure situated within a cylindrical computational domain. Several distinct sections — steam, gas flow, and pilot — are defined at the tip of the flare. Meshing was performed in ANSYS Meshing, producing 1,043,138 elements.MethodologyA flare system, or gas flare, is a combustion device used in industrial facilities such as oil and gas refineries and at oil and gas production wells, particularly on offshore platforms, to safely burn off surplus hydrocarbon gases. The Species Transport model was used to carry out this simulation.The reacting mixture is defined as an n-butane–air blend consisting of nine gaseous species: C₄H₁₀, O₂, CO₂, H₂O, H₂, CH₄, C₂H₆, C₃H₈, and N₂. The volumetric reaction model was activated to enable the chemical reactions and, in turn, the combustion process, which is represented by five distinct chemical reactions.At the flare tip, a stream of hydrocarbon gas enters the environment at a flow rate of 0.09259 kg/s. Simultaneously, a methane flow from the pilot and a steam flow from the steam inlet — both at velocities of 2.479 m/s — enter the domain to ignite the mixture. The standard k-epsilon model was used to solve the turbulent flow equations, together with the energy equation to compute the temperature variation within the combustion region.ConclusionOn completion of the solution, three-dimensional contours of velocity and of the mass fraction of each modeled gas species were obtained.For instance, examining the three-dimensional contour of carbon dioxide clearly shows that the combustion reaction and the resulting production of CO₂ are taking place. As the results also demonstrate, the mass fractions of the fuel species decrease with distance from the fuel inlet, while the mass fractions of the reaction products correspondingly increase along the same direction — confirming the progress of combustion through the domain.

Gas Flare, Two-Step Air–Methane Mechanism Combustion, ANSYS Fluent CFD Simulation TutorialDescriptionThis project simulates combustion in a gas flare, using a two-step methane–air mechanism, in the presence of a crosswind, with ANSYS Fluent.This case is a clear example of a reacting flow, where the fluid motion and the chemistry are solved together: the flow carries fuel and air into the flame, the combustion reactions release heat and change the gas composition, and the resulting temperature and density fields feed back into the flow. Modeling this coupling is exactly what the reacting-flow (species transport) approach is built for.A gas flare is a combustion device used in industrial facilities such as oil and gas refineries and at production wells, particularly on offshore platforms, to safely burn off natural gas.The 3-D geometry was built in Design Modeler. Because the flare is symmetric, only half of it is modeled to cut the computational cost, with a symmetry boundary condition applied. The flare has a cylindrical body with four outlet ducts and sits inside a computational domain that carries the wind flow; this domain is likewise halved along the symmetry plane. The model was meshed in ANSYS Meshing with 1,546,925 elements.Simulation MethodologyGas flares burn the natural gas released during oil extraction. During extraction, natural gas accumulates above the oil in the reservoir. Collecting and storing this gas is preferable, but where that is not possible it is flared. Burning the gas in a flare avoids uncontrolled, hazardous release, and converting methane to carbon dioxide before it reaches the atmosphere is less harmful than releasing the methane directly.To capture the chemistry, the species transport model is used with volumetric reactions enabled, and the eddy-dissipation model estimates the reaction rate. A methane–air mixture burns through a two-step mechanism: first methane and oxygen react to form carbon monoxide (and water), then the carbon monoxide combines with oxygen to form carbon dioxide. Air enters the domain at 0.2 m/s and 300 K, and the fuel enters at 0.1 m/s and 300 K. The realizable k-ε model and the energy equation are enabled to solve the turbulent flow and compute the temperature distribution.Results & ConclusionAfter solving, two- and three-dimensional contours of pressure, temperature, velocity, and the mass fraction of each modeled species were obtained, with the two-dimensional contours shown on the geometry's symmetry plane.The species mass-fraction contours confirm that the reaction takes place: the carbon dioxide and carbon monoxide contours show these products being generated, while the methane contour shows the hydrocarbon being consumed as the reactant. The contours also show that the crosswind carries the combustion products, such as carbon dioxide and carbon monoxide, away from the flare and disperses them into the surrounding environment.

Description: Plasma gasification is a high-temperature waste-treatment process that converts organic material into synthetic gas, using an electric arc to generate plasma hot enough to ionize and break down feedstock into syngas and an inert solid residue — a technique used to treat waste and process biomass and heavy hydrocarbons like coal and petroleum sands into usable fuel gas. This project uses ANSYS Fluent to simulate the airflow and heat distribution inside such a reactor, capturing how the hot inlet streams behave as they meet and rise toward the outlet.Methodology: The reactor is modeled in 2D in Design Modeler as a symmetrical chamber with two side inlets and a single outlet along the top edge, meshed in ANSYS Meshing with a structured grid of 8,711 elements. Hot gas enters through both side inlets at 0.1 m/s and 2000 K, exiting through the top outlet at atmospheric pressure, while the side walls are held at a fixed 600 K to represent heat loss through the chamber boundary; the case is run to convergence to resolve how the two opposing inlet streams interact and how heat is transported through the domain.Analysis: Results include 2D contours of pressure, velocity, and temperature, along with path lines and velocity vectors. Pressure drops as the flow approaches the outlet, the maximum velocity occurs at the center of the chamber where the two inlet streams collide and merge, and the highest temperatures sit at the inlets, cooling as the gas mixes and moves toward the walls. These results illustrate how colliding opposed streams shape the internal velocity and temperature fields inside the reactor, giving a clear picture of the thermal-flow behavior central to plasma gasification performance.

DescriptionExplosions in oil storage tank farms represent a persistent safety hazard in reacting flow modeling, where a rapid, energetic chemical reaction consumes fuel and releases heat along with multiple gaseous combustion products into the surrounding environment. This CFD study uses ANSYS Fluent to simulate the explosion of oil storage tanks and the subsequent dispersion of combustion pollutants across an urban area, addressing a real safety concern for regions where tank farms sit close to residential neighborhoods and industrial units. The analysis evaluates how far and in what concentrations explosion-generated pollutants such as carbon dioxide and other combustion gases reach the surrounding population, providing a basis for risk assessment and emergency planning.MethodologyThe three-dimensional urban domain, measuring 6.6 km in length, 4.6 km in width, and 200 m in height, is built in Design Modeler and includes a dedicated zone containing eighteen cylindrical oil tanks alongside separate zones representing residential and industrial districts. The domain is discretized with an unstructured mesh of 1,746,979 elements. Because the explosion involves chemical reactions among several gaseous constituents, the Species Transport model forms the core of the setup, tracking seven species — CO₂, SO₂, NO₂, CO, H₂O, C, and air, with air serving as the background fluid. The explosion is represented through defined energy and mass sources within the tank region: a heat source of 139,072.7 W/m paired with production rates for each pollutant, including CO₂ at 0.1358 kg/m³·s, H₂O at 0.0679 kg/m³·s, CO at 0.0047 kg/m³·s, SO₂ at 0.000131 kg/m³·s, C at 0.0068 kg/m³·s, and a small NO₂ contribution. Wind-driven dispersion is captured by setting the northern and western domain faces as airflow inlets and the eastern and southern faces as outlets, with air entering at 300 K and 20 m/s directed at a 60° angle, decomposed into corresponding x- and y-velocity components.Results AnalysisThe simulation produces three-dimensional contours of temperature and of the volume fraction for each gaseous species throughout the domain. Results show that the released pollutants are carried by wind into the surrounding residential and industrial zones, confirming potential population exposure following such an explosion event. The study demonstrates how species transport combined with defined energy and mass sources can reproduce the generation and atmospheric spread of combustion products, offering a practical basis for evaluating explosion hazards and informing the siting, spacing, and protection of facilities located near populated areas.