Fan Stage (Axial Flow) Aerodynamic Performance — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of an axial flow fan stage — a rotor–stator assembly that produces steady airflow for industrial applications such as cooling freshly painted body parts. The rotor's spinning blades accelerate the incoming air and induce swirl, and the stationary stator blades then straighten the flow so it exits roughly normal to the outlet. This is a classic, approachable introduction to turbomachinery CFD, and in this project you'll model both the rotating and stationary zones and evaluate the fan stage's aerodynamic performance. As the opening project of the Fan: Beginner CFD Training Package, it introduces the fan itself — its aerodynamics and the MRF rotating-zone method — establishing the foundation the fan-driven HVAC and ventilation cases build on.MethodologyThe 3D rotor–stator geometry is designed in Design Modeler with separate rotating and stationary zones defined, then meshed in ANSYS Meshing with roughly 244,675 cells. A periodic boundary condition is used to model only a slice of the fan rather than the full annulus, dramatically reducing computational cost. The MRF (Moving Reference Frame) method is set up to simulate the rotor's rotation at 1800 rpm while keeping the stator fixed — a steady-state approach that avoids the expense of a fully transient moving mesh — and the standard k-ε turbulence model is applied to the rotating flow field.AnalysisPost-processing produces 2D and 3D pressure, velocity, streamline, and velocity-vector results, clearly visualizing the swirl induced by the rotor and its correction by the stator. From these you calculate the key turbomachinery performance metrics: a rotor tip linear velocity of about 31 m/s, a Tip Speed Ratio (TSR) of 4, and an outlet airflow rate of 16.14 lit/s. Fans, compressors, pumps, and turbines all rely on rotor–stator interaction, and the MRF + periodic-boundary workflow learned here is the standard, cost-efficient approach to turbomachinery analysis — directly transferable to blowers, axial compressors, and ventilation fans. By the end of this project, you'll be able to build a rotor–stator geometry with distinct motion zones, apply periodic boundaries to model a representative slice, set up the MRF method for a rotating fan, and post-process the flow to compute the performance metrics that define fan behavior.

This project simulates the airflow inside a bladeless fan using ANSYS Fluent, with fan aerodynamics as the central theme. Unlike a conventional fan, a bladeless fan generates no airflow with moving blades; instead it draws air in and amplifies it through fluid-dynamic principles and air-multiplier technology. This brings real advantages — it is safer, with no exposed moving parts (an important benefit in homes with children or pets), and more energy efficient, since no motor is needed to spin a set of blades. The core of the study is to show how this multiplier effect arises purely from the geometry and the resulting flow field.The operating principle, as captured in the simulation geometry, proceeds in three stages. First, air intake: four square inlets, each 21 mm on a side, sit in the fan's cylindrical base of 0.2 m diameter and draw in the surrounding air. Second, air amplification: this air is forced into a 0.52 m-diameter cyclone section and channelled along an airfoil-shaped ramp, which makes it spiral and accelerate. As the flow passes over the curved upper surface of the airfoil it creates a region of negative pressure that speeds the air up and entrains far more surrounding air — multiplying the original flow roughly sixteen-fold — producing a safe, low-velocity, smooth stream without any blades. Third, air ejection: the high-speed air is expelled through a thin slit in the fan's top circular loop, giving the steady, continuous cooling stream that distinguishes a bladeless fan from the choppy output of a conventional one.The geometry was created in Design Modeler and meshed in ANSYS Meshing with 1,927,707 cells.The simulation reproduces this air-multiplier behaviour by resolving the internal flow field. From the inlet volumetric flow rate of 0.01 m³/s, the inlet velocity is 5.67 m/s. The standard k-ε turbulence model is used, which suits this application because the flow within the fan — especially through the cyclone section — is fully turbulent, a regime in which the model gives reasonably accurate predictions.The results are presented as contours, vectors and pathlines. The velocity pathlines reveal how the air is drawn into the cyclone and accelerates as it follows the airfoil ramp, while the pressure and velocity contours over the chosen planes highlight the low-pressure region generated over the airfoil and the resulting velocity distribution. As a study in fan airflow modelling, the project demonstrates how CFD can capture the air-multiplier mechanism of a bladeless fan — showing how geometry alone, through a region of negative pressure, entrains and amplifies a small intake flow into a smooth, high-volume output stream.

Series Fans CFD Simulation Using MRF Method in ANSYS FluentIntroductionThis project investigates the steady-state airflow behavior between two 3-bladed series fans rotating at an angular velocity of 300 rpm using ANSYS Fluent, employing the Multiple Reference Frame (MRF) method to capture the rotational effects of the fan blades on the surrounding flow field.Geometry and MeshThe three-dimensional geometry of the dual fan assembly was designed in SpaceClaim, and the domain was meshed using ANSYS Meshing, resulting in a total element count of 1,914,000.MethodologyThe rotation of the fans generates air suction at the inlet boundary, with a volumetric flow rate of 2.95755 m³/s. Along the domain centerline, air velocity reaches values up to 25 m/s, while the maximum velocity in the entire domain, 47.05 m/s, occurs downstream of the first fan. Turbulent flow behavior throughout the domain was resolved using the RNG k-epsilon turbulence model.Results and ConclusionTwo- and three-dimensional contours of pressure, velocity, velocity vectors, and streamlines were generated to characterize the flow field. Based on the calculated Fluent data, the air mass flow rate at the inlet equals 3.62019 kg/s. A comparison of the pressure drop across each fan reveals that the first fan produces a pressure drop roughly twice that of the second fan, at 500 Pa and 230 Pa, respectively. Negative gauge pressure is observed downstream of both fans, with the region downstream of the first fan reaching a value five times lower than that of the second fan, at -500 Pa compared to -100 Pa. Consistent with the higher pressure drop, the velocity magnitude downstream of the first fan is also higher, at 28 m/s, compared to 12 m/s downstream of the second fan, confirming that the first fan experiences a more significant aerodynamic loading within the series configuration.

Fan Heater for HVAC System — ANSYS Fluent CFD SimulationDescriptionThis project examines the performance of a fan heater and the resulting movement of heated air within a room, using ANSYS Fluent under steady-state, pressure-based solver conditions with gravity effects included. A fan heater combines two mechanisms: a heater warms the air, and a fan drives that heated air out into the room, so the flow is shaped by both forced convection (from the fan) and natural convection (from the buoyant warm air). The study captures how the heated air circulates and distributes through the space. Within the Fan: Beginner CFD Training Package, this project opens the fan-driven HVAC applications, combining a fan's airflow with heat transfer in a single room.MethodologyThe geometry was created in Design Modeler and meshed in ANSYS Meshing using an unstructured mesh, resulting in a total of 207,707 elements. Air circulating through the room passes over a heater positioned on one side, while the fan drives the heated air into the space. Turbulent flow is modeled with the RNG k-epsilon model, and the energy equation captures the temperature distribution throughout the domain. The ideal-gas equation is used to account for the variations in air density resulting from the temperature changes, so the buoyancy of the warm air is captured alongside the forced flow from the fan.AnalysisThe simulation yields contours of pressure, velocity, and temperature, among other parameters. The pressure contour shows a reduction in pressure near the heater, driven by the rise of the heated air, which moves upward through a combination of forced and natural convection. The streamline contour illustrates this flow pattern in more detail: as the air heats up, its density decreases and it rises toward the upper regions of the room; as it travels upward, it gradually loses heat, becomes denser, and eventually descends — establishing a recurring circulation pattern within the space. By the end of this project, you'll be able to set up a fan-heater simulation combining forced and natural convection, apply the ideal-gas model to capture buoyancy, and interpret the pressure, velocity, and temperature fields that describe how heated air circulates through a room.

Air Conditioning of an Office by Two Fans (HVAC) — ANSYS Fluent CFD Simulation TrainingThis project simulates the performance of fan-driven airflow inside an office for HVAC operation, with the room containing one computer and four lamps. The computer is made of plastic and acts as a heat source of 700 W/m³, while each lamp is made of glass and acts as a heat source of 2500 W/m³. Two fans mounted on the upper part of two office walls drive air into the room, and the doors and windows are assumed to exchange heat with the ambient air by convection.MethodologyThe 3D geometry was created in Design Modeler. It represents a cubic space — the office — made up of several components, including people, lamps, computers, and desks. An unstructured mesh was generated in ANSYS Meshing, with finer resolution applied to the internal components of the office, for a total of 547,820 elements.Because the fans blow air at a rapid rate, the flow is compressible, so the ideal-gas model is used to define the air. Under this model the density is not constant but varies with pressure and temperature according to the ideal-gas law. Each fan is defined in Fluent using a polynomial porous-jump condition.ResultsThe goal of the study is to examine the effect of the blown airflow on the components and people in the office, as well as its influence on the heat sources in the model. The velocity and thermal performance of the two fans are clearly visible in the corresponding contours and vectors. Given the relatively small number of heat sources, the HVAC performance of the two fans appears reasonable for this large office.

Split System: Room HVAC — ANSYS Fluent CFD SimulationDescriptionThis project uses ANSYS Fluent to simulate heated airflow distribution inside a room conditioned by a split air conditioner HVAC system, applying the fan module to model the airflow driven by the unit's two fans alongside natural buoyancy effects. A split system delivers conditioned air to a room through its indoor units, and the way that air circulates determines the comfort and temperature uniformity of the space. The simulation investigates how the heated air moves and distributes through an occupied space containing office equipment. Within the Fan: Beginner CFD Training Package, this project applies the fan module to a real split-system HVAC unit, building on the earlier fan-driven room cases toward a complete air-conditioning setup.MethodologyThe room geometry, including two split AC units and office apparatus, is built in SpaceClaim and meshed in ANSYS Meshing using an unstructured grid of 547,820 elements. The airflow from the units is modeled with the fan module, and turbulent flow is resolved using the realizable k-epsilon model, with the energy equation activated to capture the temperature distribution throughout the domain. The ideal-gas equation is applied to capture the air density variation with temperature, enabling the buoyancy effect to be modeled alongside the fan-driven forced convection.AnalysisStreamline contours reveal the resulting flow pattern, driven by a combination of forced convection from the fans and free convection from buoyancy. Heated air rises due to its reduced density, gradually cools as it reaches the upper regions of the room, and falls back down — creating the characteristic circulating flow pattern observed in the results. From these results you can evaluate how effectively the split system distributes conditioned air through the room, how temperature and airflow develop around the office equipment, and where warmer or stagnant regions form. By the end of this project, you'll be able to set up a split-system HVAC simulation using the fan module, combine forced and natural convection with the ideal-gas model, and interpret the streamline and temperature fields that describe how conditioned air circulates through an occupied room.

DescriptionThis project simulates cigarette smoke dispersion inside a smoking room using ANSYS Fluent, with an exhaust fan mounted on the upper wall and six air intakes at the base of the walls that draw in air due to the resulting negative room pressure. The room contains three occupants: a smoking woman seated on a bench near the domain's center, positioned relatively close to the exhaust fan's direction, a standing woman holding a cigarette in front of her, and a non-smoking man conversing with them nearby. The goal is to understand how air vortices shape smoke distribution in different parts of the room, which in turn informs where seating like a couch or bench should ideally be placed. The 3D geometry is built in Design Modeler and meshed in Fluent Meshing with a polyhedral grid of 965,187 elements.MethodologyCigarette smoke, treated as composed of four constituent materials, is modeled using both the Species Transport model and the Discrete Phase Model (DPM) together, capturing both the gas-phase dispersion and the discrete particulate behavior of the smoke. The exhaust fan on the ceiling is set to a negative pressure of -10 Pa to drive the room's ventilation, the energy equation is active to resolve temperature, and turbulence is handled with the standard k-epsilon model.AnalysisThe solution yields 2D and 3D contours of temperature, pressure, velocity, and smoke mass fraction, with 2D contours extracted on YZ and XZ planes through the room's center, along with time-resolved smoke pathlines. These pathlines show clearly how the combined intake and exhaust airflow shapes the smoke's movement through the room. The results indicate that seating placed closer to the exhaust fan's direction experiences a lower likelihood of air vortex formation, making that positioning preferable for reducing smoke exposure at seated locations. It's worth noting that smoke in this simulation originates only from the cigarette tips themselves; smoke inhaled and re-exhaled by occupants is not modeled, even though it could be a meaningful contributor to smoke distribution in real occupied spaces.

Greenhouse Ventilation — ANSYS Fluent CFD SimulationDescriptionThis project simulates air ventilation inside a greenhouse using ANSYS Fluent, with particular attention to how internal fans and floor heating drive air circulation. A greenhouse must maintain the right temperature and air movement for the plants inside, and this is achieved through a combination of heating and fan-driven ventilation. The simulation captures how heat from the floor and airflow from the fans together set up the circulation that distributes warmth through the space. Within the Fan: Beginner CFD Training Package, this project applies fan-driven ventilation to a large enclosed space, combining fans, floor heating, convection, and radiation in a single case.MethodologyThe three-dimensional geometry — 10 m long, 3.15 m high, and 4 m wide — is built in SpaceClaim and meshed in ANSYS Meshing with 216,456 elements. Given the time-dependent nature of the circulation process, a transient solver is used throughout. Ventilation is driven by two small fans, each 5 cm in radius, rotating at 100 rad/s inside the greenhouse. The floor is heated with a fixed heat flux of 250 W/m², while the side walls exchange heat with the outside air through convection, defined by a heat-transfer coefficient of 30 W/m²K and a free-stream temperature of 300 K. A radiation model is also activated to capture radiative heat transfer alongside convection. Turbulence and temperature distribution are resolved using the realizable k-epsilon model together with the energy equation, and air density is allowed to follow the ideal-gas law so that the buoyancy effects from heating are captured rather than assumed away.AnalysisThe resulting velocity and temperature contours show the expected buoyancy-driven behavior: air near the greenhouse floor heats up and becomes less dense over time, while the surrounding cooler air, being denser, sinks and displaces it. This density difference sets up a natural circulation pattern, which the two fans reinforce and accelerate, sustaining a continuous cycle of heat transport through the greenhouse volume. From these results you can evaluate how effectively the fans and floor heating together ventilate and warm the greenhouse, and how the temperature and airflow distribute through the space. By the end of this project, you'll be able to set up a transient greenhouse-ventilation simulation combining fans, floor heating, convection, and radiation, apply the ideal-gas model to capture buoyancy, and interpret the velocity and temperature fields that describe the circulation sustaining a healthy growing environment.

Pollution Ventilation in a Subway — DescriptionThis project simulates pollution ventilation in a subway station using ANSYS Fluent, with a focus on the station's air-conditioning system. A subway station is one of the busiest of public spaces and is therefore readily exposed to pollution. In this model, a polluting gas is defined with a molecular weight of 77.5 kg/kmol and a specific heat capacity of 1100 J/kg·K.The subway doors are treated as the sources of pollutant, since they are the points where passengers gather. The air-conditioning system is positioned on the ceiling of the station and uses its suction power to draw pollutants out into the surrounding environment. The pollutant gas enters the station at a velocity of 0.1 m/s and is carried outside by the vacuum pressure.The Species Transport model is used for the simulation, with two species defined — the air already present inside the station and the pollutant gas that enters it. The model solves the transport equations for each species. The suction at the ceiling outlet panels is defined using the Exhaust Fan boundary condition, in which a pressure jump draws the pollutant gas out of the environment. This pressure jump is set to 1,000,000 Pa.Geometry & MeshThe geometry was drawn in Design Modeler and represents a subway station comprising a subway line with rails.Setup & SolutionViscous model — RNG k-epsilon with standard wall functionsSpecies — Species Transport with 2 volumetric species (air and pollutant gas)Energy — enabledBoundary conditions — Inlet-Doors: velocity inlet at 0.1 m/s, 300 K, pollutant mass fraction 1; Inlet-Subway: pressure inlet at 0 Pa gauge, 300 K, pollutant mass fraction 0; Outlet-Panels: exhaust fan at 0 Pa gauge with a 1,000,000 Pa pressure jump; Walls: stationary, with zero heat fluxMethods — SIMPLE pressure-velocity coupling; second-order discretization for pressure; first-order upwind for momentum, turbulent kinetic energy, turbulent dissipation rate, pollutant, and energyInitialization — standard method, with an initial velocity of 0 m/s, temperature of 300 K, and pollutant mass fraction of 0ConclusionOn completion of the solution, 3D contours of pressure, velocity, and pollutant mass fraction were obtained. The pollutant contour indicates that the station's air-conditioning system performs effectively: although pollutants enter through the subway doors, they do not spread into the station space. The powerful ceiling-mounted fans of the air-conditioning system draw the contaminated air out to the external environment, keeping the station interior clear — demonstrating the role of the exhaust fan in maintaining air quality within the station.

DescriptionIn tunnel ventilation, longitudinal ventilation is the approach that offers the lowest installation and operating cost. The most common method uses jet fans, whose relatively high-velocity discharge induces airflow along the tunnel. As the air leaving the fan diffuses, it transfers energy to the tunnel airflow and raises the static pressure. Exhaust ducts then remove the hot gases and smoke produced by vehicles and by any fire from the tunnel volume; in some cases the extraction capacity may limit the longitudinal velocity in the tunnel during normal operation. Every tunnel ventilation system relies on tunnel jet fans, large axial fans, or a combination of the two to provide both pollution-control ventilation and smoke ventilation during a tunnel fire.This project presents a 3D simulation of a tunnel in which several cars are moving. Hot gases are emitted from the vehicle exhausts, and three pairs of fans mounted at the top of the tunnel extract the pollution by suction. By driving a flow in the direction of the fans, the pollutant — which rises because it is less dense than air — is carried out of the tunnel.Geometry & MeshThe domain is a 3D rectangular tunnel measuring 60 m in the X direction, 10 m in Y, and 9 m in Z. Four cars are positioned at different locations along the tunnel, and three pairs of fans are mounted on the ceiling, spaced 25 m apart. The geometry was created in SpaceClaim, and meshing was performed in ANSYS Meshing using tetrahedral elements. After importing the mesh into Fluent, the elements were converted to polyhedral, which significantly reduced their number to approximately 1,200,000.MethodologySeveral assumptions underpin the simulation: a pressure-based solver is used, the energy equation is enabled, the model is steady, and the effect of gravity is included. The jet fans are the core of the setup — they establish the longitudinal airflow that drives the smoke and pollutants toward the extraction points and out of the tunnel.ConclusionOn completion of the solution, two-dimensional contours of pressure, velocity, and the volume fractions of pollution and air were obtained, with the contours captured at every fifth iteration. The static pressure can be seen varying across different parts of the tunnel as a result of the fan action, and the streamlines trace the pollution leaving the vehicle exhausts and following its exact path toward and through the fans. Overall, the simulation demonstrates how a jet-fan longitudinal ventilation system establishes the airflow needed to control smoke and pollutants along a tunnel — the central function of the fans in maintaining safe tunnel conditions.