Manifold of Engine (Species Transport) — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of air–fuel mixing in an engine manifold using the Species Transport model without chemical reactions. The manifold has two inlets — one supplying air, one supplying a multi-component fuel gas — and three outlets, of which only one is open while the other two are blocked (treated as walls). The goal is to study how the species mix as they travel through the manifold and to evaluate the pressure on the blocked surfaces. As the opening project of the Species Transport: Beginner CFD Training Package, it introduces the model in its simplest form — tracking and mixing multiple species without chemistry — establishing the foundation the dispersion and reacting-flow cases build on.MethodologyThe three-outlet manifold fluid domain is designed in Design Modeler and meshed in ANSYS Meshing with an unstructured grid of roughly 231,646 elements. A multi-species mixture is built from the Fluent database (N₂, O₂, CO₂, CO, H₂, CH₄, H₂O), and the energy equation is activated along with the inlet diffusion and diffusion energy source options. Species mass fractions are set at each inlet — air (N₂ 0.79, O₂ 0.21) and a multi-component fuel stream (CO, CH₄, CO₂, N₂, H₂). Mass-flow inlet boundary conditions are applied — air at 0.2335 kg/s and fuel at 0.0374 kg/s — with the blocked outlets modeled as walls. The k-ε Standard model with enhanced wall treatment is used, together with PISO pressure–velocity coupling. Crucially, the Species Transport model here tracks how the multiple gas species convect, diffuse, and mix without any combustion reaction.AnalysisPost-processing examines the species distributions through the manifold, showing how the air and fuel streams mix as they travel toward the open outlet, and evaluates the outlet mixture mass flow rate (0.271 kg/s) and the pressure on the blocked outlet surfaces (771.45 Pa and 780.98 Pa). From these results you can assess the quality of the mixing and the loading on the closed surfaces. Species Transport without reactions is the foundation for mixing, intake, dilution, and ventilation analysis, and mastering multi-species mixtures and mass-fraction boundary conditions here prepares you for combustion, emissions, and any flow where gas composition matters. By the end of this project, you'll be able to build a multi-species mixture, set species mass-fraction inlet conditions, run a non-reacting Species Transport simulation, and interpret the concentration, mass-flow, and pressure results that characterize gas mixing in a manifold.

Air Freshener Spray Device CFD SimulationDescriptionThis project presents the numerical simulation of an air freshener device using ANSYS Fluent software.An air freshener is used to spray aromatic substances and is commonly found in rooms, homes, and public places. The mechanism of these devices is based on spraying: an aromatic liquid is stored inside the chamber of the air freshener and is then dispersed into the surrounding space through spraying.The geometry of the project is modeled using Design Modeler software. The geometry represents an air freshener, and the computational zone includes a sample box surrounding the device to study the spraying process within this space. The model is then meshed using ANSYS Meshing software. The mesh is unstructured, and the number of cells is equal to 357,758.MethodologyIn this project, the spraying of fragrant particles is simulated, which requires the use of the Lagrangian approach. According to this approach, the particles are tracked individually within a discrete space. For this purpose, the Discrete Phase Model (DPM) is used, and an injection is defined to disperse the discrete particles.The injection type is conical, and the particle type is droplet. The particle injection is unsteady and occurs over a period of 0.4 seconds. To make use of droplet injection, the Species Transport model is also defined, with three volumetric species: oxygen, nitrogen, and water vapor.ConclusionAfter the solution, particle tracking is studied at different points in time, and an animation of the particle injection is also obtained. By examining the particles over time, the spraying process of the device can be analyzed. The results show that the simulation is performed correctly and that the device sprays the fragrant particles effectively.

Human Cough Virus Particles in a Coffee Shop — ANSYS Fluent CFD SimulationThis project simulates the dispersion of virus-laden particles from a human cough within a coffee shop environment, using ANSYS Fluent.Geometry and MeshThe 3-D geometry was created in Design Modeler, representing the interior of a coffee shop as the computational domain. The model was meshed in ANSYS Meshing using an unstructured grid, with curvature-based refinement applied in regions requiring higher resolution. The total cell count is 4,578,388. Given the unsteady nature of the problem, a transient solver is used.MethodologyThe dispersion of virus particles is modeled using a two-way coupled Discrete Phase Model (DPM). Virus-carrying droplets are expelled from the patient's mouth through evaporating water droplets, injected at a temperature of 310 K, a velocity of 31.85 m/s, and a mass flow rate of 0.018 kg/s, over a time interval of 0 to 0.1 s.Since droplet sizes vary during dispersion, the Rosin-Rammler logarithmic distribution is used to define the diameter range, with the minimum, maximum, and mean diameters used to determine the spread parameter and the number of diameter classes per injection. The species transport model is activated alongside the droplet model to capture this behavior.For the discrete phase boundary conditions, particles passing through the patient's mouth boundary are set to "escape," meaning they leave the domain through this surface. Surfaces representing people, tables, and chairs use a "wall-film" condition, while the floor uses a "trap" condition, causing particles to accumulate on these surfaces upon contact.The simulation runs as a transient case over a duration of 3 s, with a time step of 0.01 s. Turbulence is modeled using the RNG k-epsilon model, and the energy equation is enabled to resolve the temperature field within the domain.ResultsAt the end of the simulation, particle tracking based on residence time is obtained for the final time step. An animation of the virus particle dispersion was also exported, illustrating how the particles spread throughout the coffee shop and gradually disappear over time.

DescriptionThis project simulates the HVAC system of an operating room using ANSYS Fluent, focusing on how the ventilation design manages contamination around the patient and surgical team. The system relies on laminar airflow to keep the room's air clean, with air entering from ceiling panels and moving downward through the space, sweeping contaminants, assumed to originate from the patient's body, toward the room's corners and eventually out through lower exhaust panels. A linear air curtain plays a key role in this process, forming a barrier that stops contaminated air from circulating back toward the patient once it has been displaced. The geometry, representing the hospital room and its HVAC layout, is built in Design Modeler and meshed in ANSYS Meshing with an unstructured grid of 4,137,570 cells.MethodologySince the central goal is tracking how pollutants, oxygen, nitrogen, and humidity distribute through the room simultaneously, the Species Transport model is used, solving a separate transport equation for each of these gas-phase components rather than treating the air as a single uniform species.AnalysisThe solution yields contours of velocity, pressure, temperature, and species mass fraction for both oxygen and contaminants, along with 2D velocity vector fields. The temperature contours confirm that incoming conditioned air successfully cools the region around the patient's body, which is a strong heat source, indicating the cooling function of the system is working as intended. The velocity vectors show fresh air descending from the ceiling panels and spreading sideways as it reaches the room, a pattern that initially carries contaminants toward the patient's surface before the air curtain intervenes, generating a strong flow barrier that redirects the contaminated air toward the room's sides and ultimately to the outlet panels rather than letting it return to the patient. The contaminant mass fraction contours track this same pattern closely, confirming that the HVAC system, once the air curtain effect is accounted for, effectively clears contaminants from the patient's vicinity and channels them out of the operating room.

DescriptionThis project uses ANSYS Fluent to simulate air pollutant dispersion in a street canyon between buildings, applying species transport modeling to a core urban planning and environmental engineering problem. Building geometry strongly influences how pollutants accumulate or disperse in urban street canyons, making this analysis relevant to air quality management and sustainable city design.MethodologyA 3D street canyon and building geometry is built in DesignModeler and meshed in ANSYS Meshing using a structured grid of 274,496 elements. The simulation uses a pressure-based, steady-state, incompressible solver, with the Species Transport model configured to track pollutant dispersion. Gravitational effects and appropriate boundary conditions are applied to represent realistic urban airflow.ConclusionResults include pressure, velocity, and pollutant concentration contours, characterizing how airflow patterns between buildings drive pollutant accumulation or dispersion. The analysis evaluates pollutant concentration at different locations within the urban setting, revealing how street canyon geometry and building configuration affect local air circulation and air quality — insights relevant to urban planning, traffic emissions assessment, and sustainable city design.

Pollution in a Real Urban Zone — ANSYS Fluent CFD SimulationDescriptionThis project simulates the dispersion of carbon dioxide from vehicle exhaust along an urban street using ANSYS Fluent, with species transport as the central theme. Air pollution remains a worsening problem in many developing cities, driven by ever-increasing transport demand even as emission technology improves. Tracking how a pollutant mixes and spreads through the air requires a model that resolves the concentration of each gaseous constituent separately, and that is exactly what the Species Transport model does — solving a dedicated transport equation for every component of the mixture. The core objective is to quantify how much CO₂ is dissipated across an urban zone and how free airflow influences it. Within the Species Transport: Beginner CFD Training Package, this project scales species dispersion up to a full urban zone, building on the street-between-buildings case toward city-scale pollution transport.MethodologyThe problem captures the change in carbon-dioxide mass fraction on a city street. A thin source region 0.1 m high is defined along the street to represent the integrated production of CO₂ from car exhaust, acting as a mass source within the domain at a generation rate of 4 kg/m³. Free airflow enters the surrounding urban environment at 0.2 m/s and 300 K, and the simulation examines how this airflow transports and dilutes the emitted CO₂. Because two gaseous species — air and CO₂ — are modeled, the Species Transport model is the heart of the setup. The geometry is three-dimensional, created in Design Modeler, and represents a city block comprising several buildings and a street, enclosed within a rectangular domain measuring 9 m × 13 m × 4 m, with airflow entering through three lateral faces and the 0.1 m source region sitting on one of the streets. Meshing was carried out in ANSYS Meshing with an unstructured grid of 4,137,570 elements, refined near the internal boundaries where concentration gradients are steepest. The simulation uses a pressure-based, transient solver, since the goal is to follow the change in CO₂ concentration over time. Turbulence is represented with the standard k-ε model and standard wall functions, and the energy equation is enabled to account for thermal effects. Within the species-transport framework, the inlet supplies clean air at 0.2 m/s and 300 K with zero CO₂ mass fraction, the outlet is a pressure outlet at atmospheric pressure, and the walls are treated as stationary with zero heat flux and zero diffusive flux of CO₂. Second-order discretization is used for pressure, momentum, energy, and the CO₂ transport equation to sharpen the resolution of the concentration field.AnalysisThe solution yields two-dimensional contours of pressure, temperature, velocity, and the mass fractions of air and CO₂ on XY and YZ planes, together with three-dimensional contours of the same quantities in the region of the CO₂ source. These show how the wind-driven airflow transports and dilutes the traffic-derived CO₂ as it spreads through the built environment, revealing where the pollutant concentrates and where it is effectively dispersed. A Geometry & Mesh file and a comprehensive Training Movie demonstrating how to set up the problem and extract all the results are included. By the end of this project, you'll be able to set up a transient Species Transport simulation with a defined pollutant mass source, model wind-driven dispersion through an urban geometry, and interpret the concentration fields that show how a pollutant spreads through a real city block.

DescriptionIn this project, a cooling system for a battery pack is designed using water vapor injection. The geometry consists of five battery cells arranged vertically, with a gap between the bottom of the batteries and the base of the enclosure. The mechanism at the heart of the study is species transport: air and water vapor are injected into the domain, and the mixing and transport of these species carry heat away from the cells. The geometry was created in ANSYS SpaceClaim and meshed in ANSYS Meshing using an unstructured grid, with a boundary layer applied on the battery walls to improve accuracy near these surfaces.The top and side walls are treated as insulated, while mass transfer occurs through the bottom wall. A heat flux of 3 W/m² is applied to the battery walls, and air together with water vapor at 18 °C is injected at a velocity of 0.5 m/s through nozzles on the side walls. Accordingly, the Species Transport model is employed, and the equations are solved in pseudo-transient mode.Grid Independence StudyThe mesh over the computational domain consists of tetrahedral elements with a boundary layer on the battery walls. Four grids were tested. Mesh #1, with 75,000 elements, reported an average battery-wall temperature of 20.16 °C, while Mesh #2, with 172,000 elements, reported 19.93 °C — a difference of more than 1%. A finer Mesh #3 was therefore generated, giving 19.88 °C, only about a 0.25% change from the previous grid. Mesh #2 was selected as the best-fitted grid, and Mesh #4 was also tested to confirm this choice.Mesh #Element SizeNo. of ElementsAvg. Temp (°C)Error (%)116 mm75,00020.16—28 mm172,00019.93−1.1534 mm263,00019.88−0.2542 mm990,00019.86−0.25ConclusionIn the first step, a steady simulation was performed without water vapor injection to establish the baseline. The results show that, with no cooling system applied, the batteries reach 27 °C. The standard operating range for most batteries, such as lithium-ion, is typically between 20 °C and 30 °C, though the exact range depends on the battery type and design. Introducing the water vapor cooling system reduces the battery temperature to about 20 °C — an improvement of roughly 5 degrees.The results also show that the corners of the enclosure experience higher temperatures, where hot air becomes trapped. This confirms that the placement of the nozzles has a strong influence on cooling performance and requires careful design. Overall, the study demonstrates how a species-transport approach — injecting and transporting air and water vapor through the domain — provides effective thermal management for a battery pack, keeping the cells within their safe operating range.

Steam Methane Reforming (SMR) — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of Steam Methane Reforming (SMR) — the most widely used industrial process for producing hydrogen from hydrocarbon fuels. In an SMR plant, methane reacts with steam over a catalyst to produce hydrogen, carbon monoxide, and carbon dioxide through a set of endothermic reactions, with the required heat supplied by a burner in a surrounding heating chamber. In this project, you'll model a sleeve-type SMR reactor, capturing both the catalytic reforming reactions inside the tubes and the combustion that supplies their heat — a genuinely multi-physics chemical engineering problem. Within the Species Transport: Beginner CFD Training Package, this project turns the chemistry on, moving from non-reacting species mixing into reacting flow with multiple volumetric reactions.MethodologyThe SMR plant geometry — a heating chamber plus reforming tubes — is designed in Design Modeler and meshed in ANSYS Meshing with a large unstructured grid of roughly 1.65 million elements for the complex multi-zone reactor. The Species Transport model is set up to track multiple chemical species (H₂, CO, CO₂, CH₄, O₂), with multiple volumetric reactions defined — three reforming reactions inside the tubes and one combustion reaction in the thermal chamber. A porous medium is modeled as the catalyst inside the reforming tubes, coupling the reacting flow with porous-zone behavior. The setup handles the endothermic reforming reactions and the heat coupling between the burner and the reforming tubes, so the combustion heat drives the hydrogen-producing chemistry inside the tubes.AnalysisPost-processing focuses on the mass-fraction contours of each species, verifying methane consumption and hydrogen production and confirming that the reactor is operating correctly. From these fields you can follow how the reforming reactions convert methane and steam into hydrogen along the tubes, and how the combustion in the surrounding chamber supplies the heat that sustains them. Hydrogen is central to clean energy, ammonia synthesis, and refining, and the skills built here — multi-reaction Species Transport coupled with catalytic porous zones — transfer directly to catalytic converters, fuel reformers, chemical reactors, and combustion systems across the process industries. By the end of this project, you'll be able to set up a multi-reaction Species Transport model, couple reacting flow with a catalytic porous zone, handle endothermic reactions with burner heat coupling, and interpret species contours to evaluate reactor performance.

This tutorial presents a CFD analysis of a 2-D gas turbine combustion chamber using ANSYS Fluent.A gas turbine is a rotating machine driven by the energy released during combustion. It consists of three main components: a compressor that pressurizes incoming air, a combustion chamber where fuel and air mix and ignite, and a turbine that converts the energy of the hot, expanding gases into mechanical work. Part of this mechanical output drives the compressor itself, while the remainder powers the generator in turbo-generator setups, provides thrust in turbojet and turbofan engines, or serves other applications depending on the turbine's design.The fuel delivery system is one of the most actively developed areas of gas turbine design, with injectors playing a central role in achieving efficient combustion. This project models the combustion of a methane-air mixture inside the chamber, with methane and oxygen entering at velocities of 128.9304 m/s and 12.0396 m/s, and temperatures of 286 K and 109 K, respectively. The resulting mixture ignites, releasing energy and generating heat throughout the domain.The geometry was created in Design Modeler and discretized using ANSYS Meshing, producing a structured mesh of 197,006 cells.MethodologySince the simulation involves multiple chemical species, the Species Transport model is employed to solve the transport equations for each species, while a volumetric reaction defines the combustion process. The Eddy-Dissipation model captures the interaction between turbulence and chemical kinetics, and the real gas equation accounts for density variations of the vapor phase with temperature.ResultsThe simulation outputs contours of temperature, velocity, pressure, and species mass fractions throughout the combustion chamber, confirming that the combustion reaction proceeds as expected. Concentrations of the oxidizer and fuel are highest near the inlet and decrease progressively as they are consumed in the reaction, while combustion products such as H₂O and CO start at zero and increase steadily along the chamber. As the reaction is exothermic, it releases substantial heat, driving a marked rise in chamber temperature.

Explosion — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of a TNT explosion, a problem central to engineering safety, defense applications, structural protection, and blast planning. An explosion is an extremely fast exothermic reaction that suddenly generates large volumes of hot gaseous products, producing a sharp spike in pressure and temperature and launching compression waves that propagate outward through the surrounding air. This project models the rapid decomposition of TNT, in which 2 moles of TNT generate 22 moles of gaseous products, and tracks the resulting spherical pressure wave as it propagates and dissipates across the domain. As the capstone of the Species Transport: Beginner CFD Training Package, it is the most complex reacting-flow case in the set — a rapid reaction producing a propagating blast wave.MethodologyThe module covers the underlying physics of an explosion, including the fast exothermic reaction, the sudden pressure rise, and the resulting sequence of compression and expansion waves. The computational domain is a half-sphere of 5 m radius containing a central TNT charge modeled as a 5 cm radius half-sphere, built in SpaceClaim using symmetry to reduce computational cost, and meshed with a large structured grid of approximately 2.67 million elements capable of resolving a traveling pressure wave. The problem demands a transient solver to correctly capture the moving wave front. The Species Transport model is configured with a defined species mixture and volume reaction to represent the TNT decomposition, using finite-rate turbulence-chemistry interaction with the direct source chemistry solver, the Realizable k-epsilon turbulence model, and the energy equation activated. A critical modeling decision is defining the mixture density using the ideal-gas law, which is what allows the simulation to capture the wave propagation correctly.AnalysisPost-processing generates temperature and pressure contours over time, along with an animation of the propagating compression wave, and quantifies the resulting wave speed, found to be approximately 420 m/s. From these results you can follow how the rapid exothermic reaction spikes the pressure and temperature at the charge and launches the spherical blast wave that travels outward and dissipates. Blast modeling plays a critical role in protecting buildings, vehicles, and people from explosive events, and the reacting-flow, ideal-gas, and transient workflow developed here transfers directly to detonations, deflagrations, gas explosions, and pressure-vessel safety analysis across the defense, oil and gas, and process industries. By the end of this project, you'll be able to set up a transient reacting Species Transport simulation of an explosion, configure a volume reaction with finite-rate chemistry, apply the ideal-gas density needed to capture wave propagation, and interpret the pressure and temperature fields of a blast wave.