Savonius (Two-Blade) Wind Turbine (2D) — ANSYS Fluent CFD SimulationDescriptionThis project presents a 2D CFD simulation of a Savonius wind turbine using ANSYS Fluent. The Savonius turbine is a type of vertical axis wind turbine (VAWT) used to generate electricity from wind, with curved blades mounted on a vertically positioned rotor. The most important advantage of vertical turbines is that they need no adjustment to the wind direction and can be used at low altitudes. This project simulates the airflow around a two-blade Savonius rotor to illustrate the pressure and velocity distribution and to animate the fluid motion behind the turbine.MethodologyThe geometry is produced in Design Modeler: two blades of 350 mm diameter and 25 mm thickness placed in a rotating circle of 1000 mm diameter, surrounded by an 8000 mm × 4000 mm rectangular domain. The model is meshed in ANSYS Meshing with 58,468 elements, and the transient solver is enabled to accompany the Mesh Motion option. Air enters the fluid domain at the inlet with a velocity of 10 m/s while the turbine rotates at a constant angular velocity of 40 rpm. The Mesh Motion option defines the rotating motion of the blades, and the SST k-omega model solves the turbulent flow equations, chosen for its ability to capture the flow patterns both near and far from the blade surfaces.AnalysisAfter the solution, 2D contours of pressure, velocity, and streamlines are obtained, showing how the fluid changes as it moves through the turbine blades. The results reveal distinctly different pressure and velocity distributions on the inner and outer blades. The flow enters at 10 m/s, and after colliding with the inner blade a large pressure increase occurs, so the velocity magnitude drops and reaches zero at the stagnation point — which can cause an unwanted negative torque. The outer blade, by contrast, experiences a high-velocity flow across its back that tends to push it clockwise, driving the rotation. By the end of this project, you'll be able to set up a transient 2D Mesh Motion simulation of a Savonius VAWT, define a rotating zone for the blades with the SST k-omega model, and interpret the pressure and velocity contours that reveal how the inner and outer blades contribute to the turbine's torque.

Savonius (Two-Blade) Wind Turbine (3D) — ANSYS Fluent CFD SimulationDescriptionThis project presents a 3D CFD simulation of a two-blade Savonius wind turbine using ANSYS Fluent. The Savonius turbine is a type of vertical axis wind turbine (VAWT) used to generate electricity from wind, with curved blades mounted on a vertically positioned rotor. The most important advantage of vertical turbines is that they need no adjustment to the wind direction and can be used at low altitudes. This project simulates the airflow around the rotor in three dimensions to illustrate the pressure and velocity distribution and to animate the fluid motion behind the turbine.MethodologyThe three-dimensional geometry is produced in SpaceClaim: two blades of 350 mm diameter, 25 mm thickness, and 800 mm height placed in a rotating circle of 1000 mm diameter, surrounded by an 8000 mm × 4000 mm × 800 mm cuboid domain. The model is meshed in ANSYS Meshing with 494,456 elements, and the transient solver is enabled to accompany the Mesh Motion option. Air enters the fluid domain at the inlet with a velocity of 10 m/s while the turbine rotates at a constant angular velocity of 40 rpm. The Mesh Motion model defines the rotating motion of the blades, and the SST k-omega model solves the turbulent flow equations, chosen for its ability to capture the flow patterns both near and far from the blade surfaces.AnalysisAfter the solution, contours of pressure, velocity, and streamlines are obtained, showing how the fluid changes as it moves through the turbine blades. The results reveal distinctly different pressure and velocity distributions on the inner and outer blades. The flow enters at 10 m/s, and after colliding with the inner blade a large pressure increase occurs, so the velocity magnitude drops and reaches zero at the stagnation point — which can cause an unwanted negative torque. The outer blade, by contrast, experiences a high-velocity flow across its back that tends to push it clockwise, driving the rotation. By the end of this project, you'll be able to set up a transient 3D Mesh Motion simulation of a Savonius VAWT, define a rotating zone for the blades with the SST k-omega model, and interpret the pressure and velocity results that reveal how the inner and outer blades contribute to the turbine's torque.

Vertical Axis Wind Turbine (VAWT) CFD Simulation by Mesh Motion Method, ANSYS Fluent TrainingDescriptionThis project simulates airflow around a Vertical Axis Wind Turbine (VAWT) using ANSYS Fluent. VAWTs are a class of wind turbine in which the rotor shaft is oriented vertically (perpendicular to the ground) rather than horizontally, allowing them to capture wind from any direction without needing to actively orient, or "yaw," toward the wind — a key advantage over horizontal axis turbines in turbulent or variable-direction wind environments such as urban settings.In this simulation, the turbine's three blades rotate at 2.8285 rad/s while incoming air approaches at 7 m/s, capturing how the surrounding air responds to the moving blades and revealing the associated flow parameters. A particularly important phenomenon in VAWT aerodynamics also emerges in this simulation: dynamic stall, which occurs because each blade's angle of attack relative to the oncoming flow changes continuously as it rotates around the vertical axis — unlike a horizontal axis turbine, where blade angle of attack relative to the wind stays comparatively steady. This continuously varying angle of attack can drive the flow into and out of stall multiple times per rotation, generating unsteady lift and torque fluctuations that significantly affect both turbine performance and structural loading.The 3D geometry was designed in Design Modeler and meshed in ANSYS Meshing using a hybrid mesh combining structured and unstructured regions, totaling 904,145 elements.MethodologyThe Mesh Motion method was used to model the turbine's rotational movement, physically rotating the mesh to track the blades' motion through the domain rather than relying on a rotating reference frame. The simulation was run as unsteady (transient), which is essential for capturing the time-varying dynamic stall behavior described above, with turbulence modeled using the standard k-epsilon model.ConclusionSince the primary objective was to investigate airflow behavior around the VAWT, the resulting 2D contours of pressure, velocity, and turbulent intensity provide a detailed picture of this interaction. The pressure contour shows a critical rise in air pressure directly ahead of the blade zone, corresponding to the region where each blade first meets the oncoming flow, while the velocity contour reveals wake structures forming and trailing behind the rotating blades.Together, these results characterize how the turbine's continuous rotation reshapes the surrounding flow field throughout each cycle, offering insight into the unsteady aerodynamic loading and dynamic stall behavior that distinguishes VAWT performance from that of horizontal axis designs.

Helical Wind Turbine — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of a helical wind turbine using ANSYS Fluent. The vertical axis wind turbine (VAWT) is becoming ever more important in wind power generation thanks to its adaptability for domestic installations; however, VAWTs are known to have lower efficiency, especially compared to horizontal axis wind turbines (HAWTs). To improve their performance, industries and researchers work to optimize the rotor design. This project simulates the airflow field near a helical wind turbine, investigating the airflow behavior and pressure distribution and studying the drag force.MethodologyThe geometry is drawn in Design Modeler and includes a rotary zone for the turbine walls and a stationary zone for the rest of the domain. The model is meshed in ANSYS Meshing with an unstructured grid of about 2,000,000 cells. In this simulation, the rotational motion of the turbine blades must be defined — but rather than applying rotation to the blades themselves, the rotation is applied to the field around them, which requires separating a distinct moving zone from the overall computational domain. Because a vertical axis turbine's flow is time-dependent, as the position of the blades varies over time, the Mesh Motion method is used in the cell zone conditions, with the rotation axis and rotation speed defined. The inlet wind enters at 1 m/s, and the turbine zone rotates at 120 RPM. The simulation is carried out as an unsteady (transient) analysis.AnalysisAfter the simulation, contours of velocity and pressure are obtained, along with velocity vectors around the turbine blades. The results show that the wind flow around the blades has a rotational movement, and the velocity field adjacent to the turbine wall has the highest gradient. The leading edge of the turbine wall experiences the highest pressure gradient, which is logical since the velocity there has just reached zero, and the streamlines illustrate the quality of the flow resolved in the wake — the core challenge of aerodynamic simulation. Finally, the drag force is 2.3 N, which is accurate for a turbine with the noted specifications. By the end of this project, you'll be able to set up a transient Mesh Motion simulation of a helical vertical axis wind turbine, define a rotating zone around the blades with the correct axis and speed, and interpret the velocity, pressure, and drag results that characterize helical VAWT aerodynamics.

Darrieus Wind Turbine Evaluation — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of a Darrieus wind turbine using ANSYS Fluent. The vertical axis wind turbine (VAWT) is becoming ever more important in wind power generation thanks to its adaptability for domestic installations; however, VAWTs are known to have lower efficiency, especially compared to horizontal axis wind turbines (HAWTs). To improve their performance, industries and researchers work to optimize the rotor design, and CFD is employed here to evaluate this type of turbine. The project simulates the airflow near a vertical axis Darrieus turbine, investigating the airflow behavior and pressure distribution and studying the drag force.MethodologyThe geometry is drawn in Design Modeler and includes a rotary zone for the turbine walls and a stationary zone for the rest of the domain. The model is meshed in ANSYS Meshing with an unstructured grid of 2,289,621 cells. In this simulation, the rotational motion of the turbine blades must be defined — but rather than applying rotation to the blades themselves, the rotation is applied to the field around them, which requires separating a distinct moving zone from the overall computational domain. Because a vertical axis turbine's flow is time-dependent, as the position of the blades varies over time, the Mesh Motion method is used in the cell zone conditions, with the rotation axis and rotation speed defined. The inlet wind enters at 1 m/s, and the turbine zone rotates at 120 RPM. The simulation is carried out as an unsteady (transient) analysis.AnalysisAfter the simulation, contours of velocity and pressure are obtained, along with velocity vectors around the turbine blades. The results show that the wind flow around the blades has a rotational movement, and the velocity field adjacent to the turbine wall has the highest gradient. The leading edge of the turbine wall experiences the highest pressure gradient, which is logical since the velocity there has just reached zero, and the streamline vectors illustrate the quality of the flow resolved in the wake — the core challenge of aerodynamic simulation. Finally, the drag force is 0.1826 N, which is accurate for a turbine with the noted specifications. By the end of this project, you'll be able to set up a transient Mesh Motion simulation of a vertical axis Darrieus wind turbine, define a rotating zone around the blades with the correct axis and speed, and interpret the velocity, pressure, and drag results that characterize VAWT aerodynamics.

Contra-Rotating Turbine, ANSYS Fluent CFD Simulation TrainingDescriptionThis project simulates a contra-rotating VAWT turbine using ANSYS Fluent. A contra-rotating turbine is an axial flow turbine featuring two rows of blades that rotate at equal speed but in opposite directions. This configuration allows the turbine to recover energy and power that would otherwise be lost as airflow passes through the front row of blades — in effect, using two counter-rotating blade rows in this way doubles the turbine's overall torque output compared to a single-row design.In this simulation, the Mesh Motion method defines the rotational behavior of the surrounding air. Two rows of three blades each were modeled, with a distinct airflow zone defined around each row, and mesh motion applied independently to both. Both rows rotate at 14.7 rad/s, but with their central rotation axes oriented in opposite directions — air around the upper blade row rotates clockwise, while the lower row rotates counterclockwise. Incoming airflow enters the computational domain at 5.3 m/s.Geometry & MeshThe 3D geometry was designed in Design Modeler, consisting of a rectangular cube-shaped computational domain containing the two parallel blade rows positioned in the middle, each with three blades. The domain was meshed in ANSYS Meshing using an unstructured grid totaling 3,747,546 cells.MethodologyThis steady-state simulation uses a pressure-based solver, with gravitational effects excluded. Turbulence was resolved using the standard k-epsilon model with standard wall functions for near-wall treatment. Boundary conditions included a velocity inlet at 5.3 m/s, stationary walls for both the upper and lower blade rows, a pressure outlet at 0 Pa gauge pressure, and symmetry boundaries elsewhere in the domain. The solution used SIMPLE pressure-velocity coupling with standard initialization.ConclusionResults include streamlines and 2D contours of velocity, pressure, and their respective gradients throughout the domain. The contours reveal that both pressure and velocity increase in the space between the two blade rows, correspondingly enhancing the torque and power generated at the turbine blades.Specifically, the torque applied to the upper (clockwise-rotating) blade row measured 1.89 N·m, while the lower (counterclockwise-rotating) row measured 1.93 N·m — confirming that this contra-rotating configuration distributes approximately equal torque across both blade rows, validating the design's intended balanced energy recovery between the two counter-rotating stages.

DescriptionThis project uses ANSYS Fluent to simulate boat propeller cavitation, applying the Mixture multiphase model to a critical phenomenon in marine propulsion engineering. Cavitation occurs when localized low pressure on the propeller blades causes water to vaporize, forming bubbles that collapse and erode blade surfaces while degrading propulsion efficiency. This simulation captures how cavitation forms and evolves around a rotating propeller, a key concern in naval architecture and propeller design.MethodologyThe propeller geometry is built in DesignModeler and meshed in ANSYS Meshing using an unstructured grid suited to the rotating fluid domain. The Mixture model is configured with the Schnerr-Sauer cavitation model to simulate water-vapor phase change, with appropriate vaporization pressure limits set to capture cavitation onset. Mesh motion is implemented to represent propeller rotation, paired with the SST k-omega turbulence model for accurate external flow resolution, and the analysis is run transient to capture the time-dependent development of cavitation, including super-cavitation at high rotational speeds.ConclusionResults include vapor volume fraction distributions on the propeller surfaces, pressure fields showing where cavitation initiates and grows, and the relationship between rotational speed and cavitation extent. These findings directly inform propeller design optimization — blade geometry, material selection, and operating speed — to reduce cavitation-driven erosion, noise, and vibration, supporting more efficient and durable marine propulsion systems.

DescriptionThis project investigates noise generation from a ceiling fan in a room using ANSYS Fluent, comparing two distinct acoustic modeling approaches: the Ffowcs Williams and Hawkings (FW-H) integral method and a method based directly on the wave equation. The room is a 3D square domain measuring 4 m × 3 m × 4 m, with the fan centered in the room at a height of 2.7 m. Two square openings serve as inlet and outlet, with wind entering at 3 m/s. The geometry is built in Design Modeler and meshed in ANSYS Meshing, with 720,783 cells for the FW-H case and 534,016 cells for the wave equation case; given the inherently time-dependent nature of noise generation, both cases are run transient.MethodologyIn the first configuration, the fan is set rotating at 240 rpm using the Mesh Motion method, and noise is predicted using the FW-H integral method, with several receiver points placed at different locations in the room to sample the resulting sound field. In the second configuration, the fan is held fixed while wind continues to blow through the room at 3 m/s, and the noise generated purely from the wind colliding with the stationary fan blades is captured instead through a method based on the wave equation, isolating that collision-driven noise mechanism from the rotational one modeled in the first case.AnalysisThe results include 2D and 3D contours and plots of room pressure, temperature, and velocity, along with sound pressure and amplitude plots at the defined receiver points, generated in CFD Post. Temperature and velocity fields are shown as 3D contours throughout the room, while acoustic quantities are reported both on the fan surfaces and throughout the surrounding room environment. Comparing the two methods highlights how the fan's rotation versus the wind's direct impact on a stationary fan each contribute to the overall noise generated, giving two complementary perspectives on the same acoustic problem.

Airplane Washing Using Water Jet, CFD Simulation ANSYS Fluent TrainingDescriptionAirplane fuselages accumulate contamination over time due to their high-velocity motion through the air, picking up insect residue and bird droppings that combine with engine exhaust to form a carcinogenic contaminant layer on the fuselage surface. To address this, airplanes undergo washing several times per year, with sensitive components such as windows typically covered beforehand to prevent scratching during the process.This project simulates the aircraft washing process using ANSYS Fluent. The computational domain consists of a 46×8.5×17 m cube, with a separate sub-domain modeling the aircraft's motion through this space using a sliding mesh approach. Water enters the domain through holes positioned at the bottom of a sloped inlet at 15 m/s, while air enters from the opposite side, moving against the direction of the aircraft's travel at 2 m/s, together representing more realistic washing conditions.Geometry & MeshThe computational domain was built in Design Modeler as a 46×8.5×17 m cube, with the moving aircraft sub-domain represented as a smaller cube measuring 13.5×3 m in cross-section. The domain was meshed in ANSYS Meshing using an unstructured grid, totaling approximately 4,560,000 elements.MethodologySeveral assumptions were applied to the simulation: a pressure-based solver was used, the problem was solved as transient, and gravitational effects were included.Key simulation settings included:Material properties: Water (density 998.2 kg/m³), air (density 1.225 kg/m³)Multiphase model: VOF (Volume of Fluid), with two Eulerian phases (water and air), sharp interface modeling, explicit formulation, and an air-water surface tension coefficient of 0.072 N/mBoundary conditions: Velocity inlets for water (15 m/s) and air (2 m/s); pressure outlet at 0 Pa gauge pressureCell zone conditions: Mixture fluid throughout the domainMesh motion: Moving zone with a translational velocity of 1 m/s, representing the aircraft's motion through the wash sequenceTurbulence model: Realizable k-epsilon with standard wall functionsSolution methods: SIMPLE pressure-velocity coupling, PRESTO! for pressure discretization, second-order upwind for momentum, Modified HRIC for volume fraction, and first-order upwind for turbulent kinetic energy and dissipation rateInitialization: Hybrid methodConclusionResults include volume fraction and velocity contours extracted along a longitudinal section of the computational domain. These results clearly show air injection into the domain increasing progressively over time, with the washing process itself occurring as the aircraft's moving sub-domain reaches the corresponding section of the domain — capturing how the combined water jet and airflow interact with the fuselage surface as it travels through the wash sequence.

Mixing Tank Containing Iron Powder, Transient CFD Simulation by ANSYS FluentDescriptionA mixing tank typically consists of a cylindrical vessel fitted with one or more impellers, driven by an external motor. As the impellers rotate, they generate fluid flow within the tank — either axial (moving up and down) or radial (moving outward toward the tank wall), depending on the impeller type used. This flow causes the substances within the tank to move and collide, driving the overall mixing process.This project investigates the effect of impeller rotation on the mixing of iron powder particles within a two-phase flow of water and iron powder. The closed mixing tank contains liquid water, with the impeller rotating at 120 rpm, generating a substantial vortex at the center of the tank.The 3D geometry was designed in SpaceClaim and meshed in ANSYS Meshing using an unstructured grid totaling approximately 1,260,000 elements. A boundary layer mesh with 5 layers was applied around the shaft and impeller to keep y+ values within an acceptable range in these sensitive, high-gradient regions.MethodologyA pressure-based, transient solver was used to capture the evolving interaction between the water and iron powder phases over time. The iron powder particles were defined with a density of 7800 kg/m³ and a diameter of 10 micrometers. Turbulence was resolved using the Realizable k-epsilon model, chosen for its improved accuracy in flows involving strong streamline curvature, vortices, and rotation, paired with an appropriate wall function to accurately resolve near-wall behavior around the impeller. The Eulerian multiphase model was applied with suitable interphase forces to capture the coupled fluid-particle dynamics, while impeller rotation itself was modeled using the Moving Reference Frame (MRF) method.ConclusionThe results reveal several key behaviors. Pressure contours show substantially higher water pressure ahead of the impeller compared to behind it, while axial and radial velocity contours confirm that flow speed directly in front of the impeller exceeds that found elsewhere in the domain.The y+ contours on the rotating components (shaft and impeller) fall within approximately 0 to 7.3 — confirming the selected wall function is operating correctly within its intended range. Radial velocity plotted along a line near the impeller shows a peak value of roughly 0.048 m/s occurring approximately halfway along the impeller blade, with negative values elsewhere indicating flow directed inward toward the impeller's center rather than outward.The moment on the impeller over time shows a sharp initial rise, peaking at approximately 0.00215 N·m within the first 0.08 seconds — a direct consequence of the impeller accelerating from rest — before settling into a decline that stabilizes at a constant value of approximately 0.0002 N·m by around 1.7 seconds, reflecting the system's transition from startup transient behavior to steady rotational mixing.