Discrete Phase Model (DPM) in ANSYS Fluent — CFD TrainingDescriptionThis module is a comprehensive guide to the Discrete Phase Model (DPM) in ANSYS Fluent — the framework used to simulate particle-laden flows, where discrete particles, droplets, or bubbles are tracked as they move through a continuous fluid. Rather than focusing on a single geometry, it unlocks the DPM module itself, taking you through its interface and full range of capabilities so you can set up and customize particle-tracking simulations with confidence. As the opening project of the DPM: Beginner CFD Training Package, it establishes the discrete-phase method and injection techniques that underpin every application case that follows.MethodologyThe module works systematically through the DPM setup in ANSYS Fluent. You'll learn to navigate the Discrete Phase Model dialog box, configure interaction settings and particle-treatment options, and master the tracking parameters that control a simulation. It then explores the advanced physical models available — including particle–radiation interaction, thermophoretic and Saffman lift forces, virtual-mass and pressure-gradient forces, erosion/accretion modeling, temperature-dependent effects, two-way turbulence coupling, and collision and breakup models. The injection techniques are covered in depth — single, group, surface, and cone injections, and particle types ranging from massless and inert to droplet, combusting, and multi-component — along with diameter-distribution methods for realistic particle populations. Finally, the module addresses drag laws, breakup models, turbulent dispersion through stochastic and cloud tracking, and the DPM boundary conditions that govern particle–wall interactions.AnalysisBy working through these settings, you'll build an in-depth understanding of the DPM interface and the practical skill to set up and customize particle-laden simulations, choosing the appropriate models for a given engineering problem. This forms the foundation for the practical DPM applications that follow — spray simulations with evaporation and breakup, wet combustion, erosion analysis in complex geometries, and respiratory transmission studies. By the end of this module, you'll be able to navigate the full DPM toolset in ANSYS Fluent, select suitable physical models, injection types, and drag laws for your application, and configure particle tracking and boundary conditions correctly — the essential groundwork for accurate and efficient multiphase particle modeling.

Surface Injection Using DPM — ANSYS Fluent CFD SimulationDescriptionThis project explores surface injection using the Discrete Phase Model (DPM) in ANSYS Fluent — a powerful tool for particle-laden flows across many industries. Using the Lagrangian approach, you'll simulate and analyze the behavior of particles injected from a surface, a technique essential to spray systems, combustion processes, and particle transport. Surface injection is one of the most basic ways to release particles into a domain, making it a natural first injection technique to master. Within the DPM: Beginner CFD Training Package, this project introduces the first and simplest injection method, building directly on the DPM interface lesson toward the spray and application cases that follow.MethodologyThe workflow begins with creating an optimized 3D cubic domain with surface-injection inlets in ANSYS Design Modeler, then building a structured mesh in ANSYS ICEM refined for accurate particle-flow resolution, with a final count of 92,809 elements. The simulation uses a pressure-based solver for incompressible flow, with a transient analysis and the Discrete Phase Model enabled for particle tracking, together with the gravitational effects and surface-injection parameters that govern how the particles enter and move through the domain. The DPM lies at the heart of the setup: rather than treating the particles as a continuum, it follows each particle individually along its trajectory — the Lagrangian approach that makes DPM so well suited to dispersed, particle-laden flows.AnalysisPost-processing focuses on extracting and interpreting the results: the 3D trajectories of the injected particles, how they disperse under the influence of gravity, and the injection statistics and evolution of the particle cloud over time through animated results. From these you gain a practical sense of how to tune injection parameters for a given application. The techniques are directly relevant to spray-system design, combustion and fuel injection, environmental particle dispersion, and pharmaceutical aerosol delivery — anywhere predicting where injected particles travel and how they spread is central to good design. By the end of this project, you'll be able to set up a surface-injection DPM simulation, apply gravitational and injection parameters, track particles with the Lagrangian approach, and interpret particle trajectories and cloud evolution — while understanding the advantages of Lagrangian tracking over Eulerian methods.

DescriptionThis project simulates a water spray issuing from a small circular inlet into a larger cubic enclosure, using ANSYS Fluent's Discrete Phase Model (DPM) as an introductory case for particle-tracking simulations. Unlike multiphase models that treat a second phase as continuous, DPM follows the Lagrangian approach, tracking individual droplets one by one through the surrounding air so their trajectory, velocity, and dispersion can be examined directly rather than inferred from a bulk phase-fraction field. The geometry is a rectangular cube with a circular inlet on the top wall, built in Design Modeler and meshed in ANSYS Meshing with an unstructured grid of 25,464 cells.MethodologyBecause the droplets move as discrete entities through a continuous air medium, the case couples a Lagrangian DPM formulation to the continuous Eulerian air flow, run transient so the spray's development in time can be captured. The core setup step is the injection definition: water is introduced as a surface injection from the inlet, with droplets treated as inert particles, meaning their size, position, and velocity at entry are specified directly and Fluent integrates each individual trajectory through the resolved flow field, in contrast to a multiphase model where phase behavior would instead be governed by shared momentum and volume-fraction equations.AnalysisThe results include velocity and mass-concentration contours of the water particles at the final time step, along with 3D particle tracks colored by speed and droplet diameter. These tracks confirm the injection is behaving as intended, with droplets dispersing discretely from the top inlet and spreading through the enclosure, the exact behavior relevant to tasks like sizing spray nozzles or predicting coverage patterns in a real application.

Color Spraying on a Wall with Conical Injection — ANSYS Fluent CFD SimulationDescriptionThis project simulates color (paint) spraying onto a wall using a conical injection in ANSYS Fluent. The discrete phase is modeled with a one-way coupled DPM approach, in which the continuous phase influences the particles but the particles do not feed back on the flow. The injection is of the cone type, with a particle velocity of 10 m/s and a cone angle of 30 degrees.Geometry & MeshThe 3D geometry was created in SpaceClaim. The computational domain is 3 m long, 3 m wide, and 4 m high. The mesh was generated in ANSYS Meshing using an unstructured grid, with a total of 254,934 cells.Several assumptions underpin the simulation: the solver is pressure-based, the simulation is unsteady (time-dependent), and the effect of gravity is neglected.MethodologyThe problem setup is summarized below:Viscous model — laminarDiscrete phase — enabled, with unsteady particle tracking; the injected material is the color spray, the particle type is inert, and the injection type is a coneBoundary conditions — the side wall and back wall are stationary, with the discrete phase condition set to escape; the top wall is stationary, with the discrete phase condition set to trapSolution methods — SIMPLE pressure-velocity coupling; second-order discretization for pressure, second-order upwind for momentum, and first-order upwind for the modified turbulent viscosityInitialization — standard methodConclusionIn this simulation, the spray paint deposited on the wall is modeled using an injector that introduces the particles in a conical pattern. The cone angle governs the spread and range of motion of the particles, determining how they disperse from the nozzle and where they ultimately strike the wall — with the trap condition capturing the particles that reach the target surface and the escape condition allowing them to exit elsewhere in the domain.

Discrete Phase Flow Trap (Trapper) by Gravity — ANSYS Fluent CFD SimulationDescriptionThis project explores the dynamics of particle trapping in a gravity-driven flow system using the Discrete Phase Model (DPM) in ANSYS Fluent. The goal is to understand how particles carried in a fluid can be separated and captured — a trapping scenario in which gravity, the fluid flow, and the particle properties together determine which particles are trapped and which pass through. It's a practical application of particle-fluid interaction and separation, directly relevant to air and water purification, industrial filtration, and particulate-matter control. Within the DPM: Beginner CFD Training Package, this project applies the discrete-phase method to a simple, self-contained particle-separation problem, putting the injection and tracking skills from the method module to work.MethodologyThe setup centers on the Discrete Phase Model, representing particle behavior through defined injection methods, size distributions, and material properties. The gravity-driven fluid flow is modeled with the appropriate body-force terms and pressure-gradient considerations, and two-way coupling between the discrete particles and the continuous fluid is included to capture their mutual influence on momentum and energy transfer. A turbulence model is applied together with turbulent-dispersion effects on the particle trajectories, and boundary conditions are configured for both phases — inlet flow conditions, particle injection parameters, and outlet conditions. Convergence is managed with appropriate under-relaxation factors, time-step sizing for particle tracking, and residual scaling.AnalysisPost-processing uses ANSYS Fluent's tools to analyze the particle trajectories, trapping efficiency, fluid flow patterns, and particle-concentration distributions, with visualization techniques suited to discrete-phase simulations. From these results you can see which particles are captured and which escape, evaluate the trapping efficiency of the system, and understand how the gravity-driven flow and particle properties govern the separation. By the end of this project, you'll be able to set up a gravity-driven DPM simulation with two-way particle–fluid coupling, configure injections and boundary conditions for a separation problem, apply convergence strategies specific to particle tracking, and interpret trajectories and trapping efficiency — skills that transfer directly to the design of particle-trapping and separation systems in environmental and process engineering.

This research examined snowfall patterns within a park environment utilizing the Discrete Phase Material (DPM) approach. The simulation incorporated two material types: air as the continuous phase and discrete snow particles. Particle movement trajectories throughout the park space were tracked and analyzed using Ansys Fluent computational software.Modeling ApproachThe three-dimensional geometric model was developed through Spaceclim software. For computational analysis, an unstructured mesh containing 1,553,972 elements was created in the Ansys meshing module, with the Curvature Method applied to enhance resolution in areas requiring greater computational precision.Simulation ParametersThe computational model operated under several key assumptions:Flow equations were not solvedTime-dependent (transient) simulation approachGravitational acceleration of 9.81 m/s² applied downward along the y-axisThe DPM configuration included:Surface velocity inlet injectionRosin-Rammler diameter distributionParticle diameter range: 1×10⁻⁴m (minimum, mean, and maximum)Mass flow rate: 1×10⁻²⁰ kg/sMaterial properties included air and inert particles with density of 1550 kg/m³Boundary ConditionsInlet: Velocity inlet (0 m/s) with DPM escape conditionSymmetry conditions applied to symmetrical boundariesWall conditions (stationary, no-slip, wall film) applied to bench, ground, leaves, road, and wood elementsStandard initialization method implementedThe simulation results yielded particle tracking data throughout the park environment, with accompanying snowfall animation documentation.

Dust Particles Entering the Room — ANSYS Fluent CFD SimulationDescriptionThis project uses ANSYS Fluent to study how dust particles enter a room through windows and move and deposit inside. Dust-laden air drawn in through the windows carries particles that then disperse, settle, and accumulate within the space — a practical problem for indoor air quality, cleanliness, and ventilation design. The simulation captures both the airflow through the room and the transport and deposition of the dust particles it carries. Within the DPM: Beginner CFD Training Package, this project applies the discrete-phase method to indoor particle transport, building on the injection cases toward a real environmental application.MethodologyThe 3D geometry, built in DesignModeler, represents a room with two windows and a chimney, meshed in ANSYS Meshing with 42,061 elements. Because the deposition evolves over time, the simulation is transient. Dust-laden air enters through the two window inlets at 0.25 m/s and exits through a pressure outlet at the chimney top. Particle transport and settling are modeled with a two-way coupled Discrete Phase Model (DPM) to capture the interaction between the particles and the carrier flow, and the laminar flow model is used for the continuous phase.AnalysisThe outputs include 2D velocity contours, vectors, and streamlines, revealing the airflow paths and the dust motion through the room. The wind-driven flow carries particles along the main stream, while recirculation zones promote enhanced deposition and sediment accumulation — showing where dust is most likely to collect. By the end of this project, you'll be able to set up a transient two-way coupled DPM simulation of indoor particle transport, define particle-laden inlets and deposition behavior, and interpret the flow and particle results to understand where dust disperses and settles within a room.

Asthma Spray Inhaler Injection into the Lung — ANSYS Fluent CFD SimulationDescriptionThis project simulates the delivery of an asthma spray into human lungs using ANSYS Fluent. When a patient uses an inhaler, aerosol particles are carried on the inhaled airstream deep into the branching passages of the lung, and where those particles travel and deposit determines how effectively the medication reaches its target. The simulation captures the inhaled airflow through a lung model and tracks the aerosol particles it carries, assessing their transport and deposition. Within the DPM: Beginner CFD Training Package, this project introduces biomedical particle deposition, applying the discrete-phase method to a real respiratory drug-delivery problem.MethodologyThe 3D geometry, built in SpaceClaim, represents a simplified lung model with a 50 cm inlet diameter, meshed in ANSYS Meshing with 3,734,238 elements. Given the time-dependent nature of inhalation and particle motion, a transient solver is used. A one-way coupled Discrete Phase Model (DPM) tracks the aerosol particles moving through the continuous air phase. Air enters at 5 m/s, with gravity set to −9.81 m/s² along the z-axis, and particles of 100 µm diameter are introduced through a surface-velocity injection at the inlet. Turbulence is resolved with the realizable k–ε model, and the particle trajectories inside the lung domain are computed and visualized to assess transport and deposition behavior.AnalysisPost-processing provides 2D and 3D contours of velocity and pressure, along with an animation of particle tracks throughout the lungs, illustrating the spray's distribution following inhalation. From these results you can see how the inhaled air carries the aerosol through the lung passages and where the particles are likely to deposit — the key measure of how well the medication is delivered. By the end of this project, you'll be able to set up a transient one-way coupled DPM simulation of aerosol delivery, define a surface-velocity particle injection, resolve the carrier airflow with an appropriate turbulence model, and interpret the particle trajectories that characterize drug deposition in the lung.

DescriptionAirborne droplet transmission during speech is a key application of the Discrete Phase Model within Fluent, where dispersed particles must be tracked as a distinct phase moving through a continuous air field. This CFD study uses ANSYS Fluent to simulate coronavirus-laden droplets released during speech at sub-social-distance separations, modeling exhaled particles from an infected speaker and their transport toward another person within a defined indoor volume, in order to assess transmission risk while talking.MethodologyThe three-dimensional domain, measuring 1.6 m × 2 m × 2.6 m, is built in DesignModeler with two individuals facing each other 0.8 m apart, with the infected person's mouth defined as the particle source. The domain is discretized in ANSYS Meshing into 724,076 elements, and a transient solver is used to capture the time-evolving dispersion. The Discrete Phase Model is applied with unsteady particle tracking at a 0.001 s time step, treating exhaled droplets as a dispersed phase within the continuous air field. An injection is defined at the mouth surface using inert particles of 1×10⁻⁶ m diameter at 310 K, released over a 0 to 20 s window, with a custom profile prescribing particle velocity and mass flow rate: a sinusoidal velocity history peaking at 0.33 m/s, with mass flow rate scaled proportionally to that velocity. Turbulence is modeled using RNG k–ε, and the energy equation is solved to capture temperature effects on the flow.Results AnalysisPost-processing provides particle tracks at multiple time instances, reported in terms of residence time and instantaneous velocity. Results show particle emission occurring during the initial 20 s, after which only previously emitted particles continue moving within the gap between the two individuals. The simulation indicates that speaking for 20 s without a mask can result in particles reaching the other person by approximately 40 s, illustrating a potential exposure pathway relevant to airborne transmission risk assessment.

DescriptionThis project simulates erosion in a 90-degree pipe elbow (knee) using ANSYS Fluent, investigated through CFD analysis. Erosion in bends is a critical concern in the gas and petrochemical industry, where pipelines routinely transport fluids carrying entrained solid particles over long distances.In a straight run of pipe, fluid impurities pose little problem. The difficulty arises when the flow changes direction: the suspended solid particles, owing to their inertia, cannot follow the fluid streamlines through the turn. This causes the particles to decouple locally from the carrier fluid and strike the pipe wall, gradually wearing away the material — the phenomenon known as erosion.In practice, industrial fluids are almost never pure, so erosion is an unavoidable challenge in pipeline transport. Flow turbulence intensifies the effect: the more turbulent the flow, the greater the momentum carried by the particles, and the harsher their impact on the wall. These impacts are most severe wherever the flow changes direction, which is exactly why erosion is concentrated at bends and elbows. Beyond turbulence, several other factors govern the extent and pattern of erosion, including particle size, particle mass flow rate, the redirection of the particle path, the number of wall impacts, and the overall flow rate.Because erosion tends to occur precisely where the flow redirects, fittings and joints — particularly elbows — are the primary locations examined when assessing erosion in a pipeline network.MethodologyEvery simulation begins by defining the computational domain. Although the geometry is a single elbow joint, it was subdivided into separate sections to enable a structured mesh, with each segment meshed individually so that boundary-layer settings could be applied precisely.The 3D geometry was created in ANSYS Design Modeler, and meshing was performed in ANSYS Meshing. The domain was split into four parts, each meshed with a structured grid. A structured mesh offers faster and more accurate CFD solutions — an advantage that matters greatly for erosion studies, since the boundary layer, path lines, and particle tracking must all be resolved cleanly as the flow travels through the bend. The final mesh contains 4,319,695 elements.Because the mesh was sufficiently fine, the Enhanced Wall Treatment method was used in place of standard Wall Functions for near-wall modeling, providing higher accuracy at the boundaries. The Discrete Phase Model (DPM) was applied to represent the solid particles carried within the pipeline.ConclusionAn important consideration is that the upstream pipe length must be long enough for the flow to fully develop before reaching the elbow; otherwise, the particle distribution entering the bend may yield unrealistic results. The velocity magnitudes of both the fluid and the particles can be readily examined from the corresponding contours.In addition, the particle concentration and — most importantly — the erosion contour are presented, offering a comprehensive picture of erosion behavior in pipeline bends.