This project simulates the early stage of aircraft icing — the formation of a thin liquid water film on an airfoil surface as humid air laden with supercooled water droplets flows over it. The motivation is directly safety-driven: once this film forms, at low enough temperatures it can freeze on the wing, degrading lift and control. Predicting where and how thick the film forms is the first step in any anti-icing or de-icing design.The physics is handled with the Eulerian Wall Film (EWF) model, layered on a Eulerian multiphase setup where air is the primary phase and liquid water droplets are the secondary phase, also defined as the constituent of the wall film. The EWF model is purpose-built to track the formation, thickness, and flow of a thin liquid layer along wall surfaces — and unlike VOF, it can impose and correct the film's initial wall conditions, giving cleaner control over the film-wall interaction. Note that EWF is a 3-D-only model and requires the Eulerian multiphase model to be active, which sets the structure of the whole case.Setup: the air–droplet mixture approaches the airfoil at 30 m/s and 250 K, with a droplet volume fraction of 0.002. The airfoil wall is initialized with a film of specified height and zero velocity, and the case is run transient for 1 s at a tight time step of 1×10⁻⁴ s to resolve the film's growth and motion. Geometry is built in Design Modeler and meshed in ANSYS Meshing as an unstructured mesh (~978,532 elements).What the results show: contours of density, pressure, air and water velocity, and air/water volume fractions, plus the key output — the film-thickness contour on the airfoil body — all at the final second. The thickness map reveals where impinging droplets accumulate into a film, which is exactly the region most at risk of freezing and the target for any icing-protection system.You'll learn to: activate and configure the Eulerian Wall Film model on top of a Eulerian multiphase case, define droplet-laden inflow and a film-initialized wall, run a fine-time-step transient icing case, and read film accumulation from thickness and volume-fraction contours.

DescriptionThis project uses ANSYS Fluent to simulate aeroacoustic sound generation around a NACA0012 airfoil, a key application of the acoustic module in aerospace engineering. Sound waves generated by aerospace components like airfoils are a significant concern in aircraft noise and acoustic design. This study examines how acoustic behavior changes across three angles of attack — 0°, 7°, and 14° — as airflow at 68 m/s passes over the airfoil.MethodologyThe 2D geometry is built in DesignModeler, with the NACA0012 airfoil coordinates imported as a point cloud from Airfoil Tools. The airfoil has a 1 m chord length and sits within a computational domain measuring 400 m × 200 m. The domain is meshed in ANSYS Meshing using a structured grid of 231,840 elements. The Broadband Noise Sources model is used to define the acoustic behavior, with reference values set to standard air density (1.225 kg/m³), speed of sound (340 m/s), and reference acoustic power (1e-12 Pa).ConclusionResults include 2D pressure and velocity contours, along with velocity and acoustic power level plots across all three angles of attack, tracking sound pressure from a few meters upstream of the airfoil, along its surface, and downstream. The sound wave is shown to originate after airflow impinges on the airfoil body. At zero angle of attack, sound propagates further downstream, while higher angles of attack concentrate the sound amplitude closer to the airfoil, indicating a more limited propagation distance.

DescriptionThis project simulates the use of Dielectric Barrier Discharge (DBD) plasma actuators to prevent boundary layer separation on a NACA 0012 airfoil using ANSYS Fluent. Flow separation on the suction side of an airfoil reduces lift, increases drag, and in severe cases causes stall, all driven by the boundary layer losing enough energy to detach from the surface. DBD actuators address this without moving parts: a high voltage difference between cathode and anode ionizes the surrounding air into plasma, generating an electrical current that in turn produces a magnetic field, which acts on the ions in the boundary layer and adds momentum back into the flow, suppressing separation. The airfoil has a chord length of 0.1 m and carries two DBD actuators, one near the point of maximum thickness and one near the trailing edge. Two flow cases are studied: 50 m/s at 15° angle of attack, and 20 m/s at 12° angle of attack. The geometry is built in SpaceClaim and meshed in ANSYS Meshing with a structured grid of 463,701 elements.MethodologyTurbulence is resolved with the k-epsilon model, and the energy equation is active. The electromagnetic physics — voltage distribution, and the x and y components of the magnetic vector potential — are introduced through three User-Defined Scalars (UDS), with their steady-state transport equations solved alongside the flow equations. A source term in the magnetic field transport equations is added via a UDF, using an electrical diffusion coefficient of 0.5 for ionized air and a magnetic permeability of 1.2566×10⁻⁴. Current density components are computed from the potential field, and the resulting electromagnetic body forces are fed back into the flow through three additional source terms: one each in the energy equation, x-momentum equation, and y-momentum equation, all implemented via UDFs. User-Defined Memory (UDM) is used to store and expose the current density vector for post-processing. Air density follows the ideal gas law throughout.AnalysisVelocity and pressure contours around the airfoil, along with velocity vectors, are obtained for both flow cases, confirming that the plasma-induced body force effectively suppresses boundary layer separation that would otherwise occur at these angles of attack. Lift coefficient results and surface pressure distributions along the airfoil are reported for each case, quantifying how much the DBD actuation improves aerodynamic performance relative to an uncontrolled baseline, and demonstrating that the UDF-based electromagnetic coupling is delivering the intended momentum addition to the boundary layer.

DescriptionIn this project, we present a simulation of an Airfoil exposed to the airflow via ANSYS Fluent software.Since the airfoil is exposed to airflow, an interaction occurs between the wind blowing and the airfoil structure. It means that airflow exerts a volume force on the airfoil's body by hitting it. Therefore, we intend to perform a numerical simulation of the airfoil as a Fluid-Structure Interaction (called FSI).The interaction between fluid and structure can be implemented as:One-way FSITwo-way FSIIn this project, we aim to analyze only the effect of fluid on the structure, and there is no need to account for the effect of the structure on the fluid. So, we choose One-way FSI, which is a simple and less-expensive approach.We modeled the geometry via SpaceClaim software. The computational domain is a sample space of the surrounding air that includes both fluid and solid domains. There is a solid airfoil structure within the fluid environment, which is considered fixed from the center.We meshed the computational domain via ANSYS Meshing software. The mesh is of an unstructured type, and approximately 1,700,000 cells have been generated.MethodologyFluid-structure interaction can be performed in two general methodologies:In the ANSYS Workbench environment, using an external solver (specifically, system coupling)Only in the Fluent solver (in the form of an intrinsic FSI).In this project, we implemented a one-way FSI in the ANSYS Fluent environment. In other words, the Fluent solver performs both fluid and solid calculations simultaneously.For two-way FSI in Fluent solver, the Structure model is utilized. The structural model can be implemented in two ways:Linear elasticity: The deformation is proportional to the applied force. In this case, the deformations are usually small, and the calculation process is faster.Nonlinear elasticity: The deformation is not necessarily proportional to the applied force. In this case, the deformations are usually large, and the calculation process is more complex and time-consuming.In this project, we considered fluid-structure interaction in the form of a Linear Elasticity state.Since we were analyzing one-way FSI and not considering the effect of structural displacement on the adjacent fluid, we didn't need to use the dynamic mesh model.ResultsWe analyzed the results in two fluid and solid approaches:In a fluid view, we studied the behavior of airflow. For this, we obtained the distributions of the pressure and velocity of air. The results show that the airflow collides with the airfoil body at high speed and, as a result, exerts a hydraulic force on the airfoil structure.In a solid view, we studied the behavior of the airfoil body under the influence of the applied forces of the air flow. For this, we obtained the distribution of the von Mises stress and displacements (in all directions). The results confirm that the airflow affects the airfoil structure and, as a result, it undergoes displacements relative to the fixed center.In conclusion, we can claim that we carried out the simulation project of an airfoil correctly and acceptably by using the two-way FSI method.

DescriptionThis project simulates supersonic inviscid flow over an F-16 fighter aircraft using ANSYS Fluent. Flying at 400 m/s — approximately Mach 1.16, comfortably above the speed of sound — the aircraft experiences a flow field dominated by pressure and inertial effects rather than viscosity. By treating the fluid as inviscid (zero shear stress), the simulation isolates the pressure-driven physics responsible for aerodynamic lift, making it a clear illustration of the fundamentals of high-speed external aerodynamics.Since supersonic flow is inherently compressible, the Mach number serves as the key parameter quantifying this compressibility throughout the simulation. Treating the flow as inviscid simplifies the governing Navier-Stokes equations toward Bernoulli's equation, allowing the pressure and velocity fields to be resolved without the added cost of capturing boundary-layer effects.The 3D F-16 aircraft geometry was imported and positioned within a flow enclosure using SpaceClaim, and the surrounding domain was meshed in Fluent Meshing using an unstructured grid of approximately 979,000 elements.MethodologyThe simulation employs the inviscid viscous model, with air density defined via the ideal gas law to appropriately capture compressible behavior at supersonic speed.A key methodological choice in this simulation is the use of a pressure-based solver with coupled pressure-velocity coupling, rather than the more commonly expected density-based solver typically used for supersonic cases. This approach helps avoid common convergence difficulties that can arise at supersonic speeds, offering a more robust path to a converged solution for this geometry.ConclusionPost-processed pressure and velocity contours reveal the high-pressure region forming beneath the wings — the primary source of aerodynamic lift in this configuration. The results also illustrate the tightly coupled relationship between pressure, density, and temperature that characterizes compressible flow behavior.Inviscid supersonic analysis of this kind provides a fast, computationally efficient first step in aircraft and missile aerodynamic design, delivering lift and pressure distribution insights without the added cost of resolving boundary layers. The pressure-based solver technique demonstrated here is a genuinely useful approach for stabilizing otherwise difficult high-speed compressible simulations.

Bullet (HPBT) Movement (Dynamic Mesh) — ANSYS Fluent CFD SimulationDescriptionThis project simulates the movement of a Hollow Point Boat Tail (HPBT) bullet using dynamic mesh in ANSYS Fluent, exploring high-speed projectile dynamics. As the bullet travels at supersonic speed, it forms shock waves that govern its aerodynamic performance, and capturing this means letting the bullet move freely through the domain while the mesh deforms and regenerates to follow it. Because the flow is supersonic and compressible, the case also brings in the density-based solver and the shock physics that define high-speed aerodynamics. Within the Dynamic Mesh: Beginner CFD Training Package, this project combines moving-body dynamic mesh with compressible supersonic flow, adding shock-wave physics to the moving-body cases before it.MethodologyThe optimized 2D HPBT bullet geometry is created in ANSYS Design Modeler and meshed in ANSYS Meshing with an unstructured grid of 13,040 elements suited to dynamic remeshing. A density-based solver is set up for the compressible, transient flow, and the dynamic mesh model is configured for the bullet's movement at Mach 2.531, with ideal-gas properties assigned to the air to model the compressibility effects. As the bullet moves, the dynamic mesh deforms and regenerates to follow it, keeping the solution valid throughout the motion.AnalysisPost-processing extracts pressure, temperature, and velocity contours, revealing the supersonic flow around the moving bullet and the formation and propagation of the shock waves behind it. The mesh deformation and regeneration are evaluated to confirm the dynamic-mesh approach captures the transient flow correctly, and the compressibility effects are assessed to show why a density-based solver is essential at supersonic speed. From these results you can understand how the shock structure shapes the bullet's aerodynamic performance. By the end of this project, you'll be able to set up a dynamic-mesh simulation coupled with a density-based compressible solver, model a projectile moving at supersonic speed, and interpret the shock waves and pressure fields that govern high-speed projectile aerodynamics.

DescriptionThis project simulates aeroacoustic noise generation around an Audi car body, comparing configurations with and without a rear spoiler, using ANSYS Fluent. Aeroacoustics studies how sound arises from turbulent fluid motion and from aerodynamic forces striking surfaces; turbulent flow carries oscillating pressure and density gradients, and it's these oscillations, propagating as pressure waves, that constitute the generated sound. The subject matters well beyond automotive design, since the same mechanisms govern the very high noise levels produced around aerospace surfaces like airfoils. The car geometries, both with and without spoiler, are built in three dimensions in Design Modeler and meshed in ICEM, with airflow directed at the body at 70 m/s.MethodologyTurbulence is resolved with the SST k-omega model, and the acoustic field is predicted using Fluent's Broadband Noise Sources model, which derives sound generation from the statistics of the turbulent flow rather than resolving acoustic waves directly. The acoustic setup uses standard air properties as reference: a density of 1.225 kg/m³, a sound speed of 340 m/s, and a reference acoustic power of 1×10⁻¹² Pa. Both the spoiler and no-spoiler configurations are run under identical inflow conditions so the two cases can be compared directly.AnalysisThe solution yields 2D pressure and velocity contours for both configurations, along with plots of velocity and acoustic power level along the car's longitudinal axis, sampled from a few meters upstream, across the car body, to a few meters downstream. These results show that adding the spoiler noticeably reduces the acoustic power generated by the airflow striking the body, from roughly 95 dB without the spoiler to about 70 dB with it. Interestingly, this trend reverses in the far wake behind the car, where the spoiler configuration actually shows higher acoustic power than the case without one, suggesting the spoiler suppresses near-body noise generation at the cost of somewhat more turbulent, noise-generating structure further downstream.

DescriptionThis project simulates the airflow over the impeller of an electric motor using ANSYS Fluent, investigated through CFD analysis. In an electric motor, this impeller acts as a cooling fan, driving air over the machine to carry away the heat generated by electrical losses in the windings and core — making its aerodynamic performance an important consideration in electrical and power machine design, since a motor's temperature limits its continuous rating, efficiency, and insulation life.Turbomachines, also known as fluid machines, are widely used across industry, so understanding their behavior in the surrounding fluid is essential. They fall into two broad categories: the first transfers energy to the fluid, while the second extracts energy from the fluid and delivers it to the system in various forms. Fans and compressors belong to the first group, while wind and water turbines belong to the second. An electric-motor impeller is itself a turbomachine of the first type, and studying the motion of its blades within the surrounding flow helps analyze its behavior and ultimately improve the design and material selection of the blades.Here, the airflow over the impeller is examined. Air enters the computational domain at 80 m/s, and the impeller rotates at 1000 rpm. The geometry was created in Design Modeler and meshed in ANSYS Meshing using an unstructured grid of 1,786,708 cells.MethodologyThe rotation of the impeller is modeled using the Multiple Reference Frame (MRF), or Frame Motion, approach. In this method, the fluid around the impeller blades is treated as rotating while the blades themselves are held stationary, with the rotational velocity of the fluid set equal to that of the impeller. This is applied through the MRF tool in the Cell Zone Conditions — an efficient way to capture the steady rotating-blade behavior without physically moving the mesh.ConclusionOn completion of the solution, contours of pressure, velocity, and temperature were obtained, along with pathlines and velocity vectors around the blades. The pathlines clearly reveal the rotational motion of the flow around the impeller. The pressure contour shows higher pressure on the front face of the impeller, where it meets the incoming airflow, and a large pressure drop behind it. The velocity contour shows the velocity increasing radially, reaching its maximum around the blade tips — a clear signature of the impeller's rotation.Together, these results characterize how the impeller moves air through the motor, providing the kind of insight into cooling airflow and blade loading that supports the thermal management and design of electrical machines.

DescriptionThis project investigates the airflow over a Horizontal Axis Wind Turbine (HAWT) using ANSYS Fluent, with the aim of studying the velocity and pressure distribution across the blade surfaces and body. As the dominant technology in modern wind power, the HAWT is a cornerstone of renewable energy engineering, where analyzing blade aerodynamics is essential to maximizing the energy captured from the wind.The 3D model was created in SOLIDWORKS and imported into Design Modeler. The turbine consists of three blades, a rotary axis, and a surrounding flow domain. Meshing was performed in ANSYS Meshing using a structured grid of 4,270,222 elements.MethodologyThe simulation aims to examine the effect of the wind on the turbine blades and to calculate the drag and lift forces acting on the blade surfaces. The blades rotate about the horizontal axis at a rotational speed of 72 rad/s, while the air surrounding them is treated as stationary.Using the Multiple Reference Frame (MRF) method, the blades are held fixed and the air region around them is assigned a rotating frame turning at the same 72 rad/s about the y-axis. Because this is an external-flow problem, the k-omega SST model is used; this hybrid formulation blends the k-omega model in the near-wall regions with the k-epsilon model in the free stream beyond the boundary layer. Air enters the domain at a velocity of 15 m/s and exits through a pressure-outlet boundary at atmospheric pressure.ConclusionOn completion of the solution, contours of velocity, streamlines, and velocity vectors were obtained. The velocity contour clearly reveals the radial distribution of the airflow produced by the rotating blades, while the velocity vectors near the blade surfaces show, in detail, the interaction between the wind and the turbine blade. Together, these results illustrate how the blade extracts energy from the incoming wind — the fundamental aerodynamic behavior that governs the performance of a wind turbine in renewable energy applications.

H-Type Vertical Axis Wind Turbine (VAWT), Mesh Motion — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of an H-type vertical axis wind turbine (VAWT) using ANSYS Fluent's Mesh Motion method. Turbines are a reliable, clean source of electricity generated by wind-induced rotation, but wind farms face challenges such as the low efficiency of horizontal axis turbines (HAWTs) at smaller diameters, the disruption of natural landscape views, and low wind conditions. Vertical axis turbines (VAWTs) address these issues: they avoid the very large diameters (up to 200 m) common in HAWTs, are widely used offshore where they don't disrupt valley views, and benefit from the more predictable, reliable wind of offshore sites. The H-type turbine analyzed here has six blades, with three positioned closer to the center of rotation.MethodologyThe geometry is drawn in Design Modeler and meshed in ANSYS Meshing with an unstructured grid of 1,546,624 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 blade positions vary over time, the Mesh Motion method is used in the cell zone conditions, with the rotation axis and rotation speed defined. The turbine rotates in the −Z direction at an angular velocity of 14.17 rad/s, and the air enters the domain at 5.3 m/s. The simulation is carried out as an unsteady (transient) analysis.AnalysisAfter the simulation, contours of velocity and pressure are obtained, along with velocity vectors and pathlines around the turbine blades. The results show that the airflow around the blades has a rotational movement, dominated by the turbine's rotation, with a maximum air velocity of 45 m/s captured downstream of the turbine and an inlet air mass flow rate of 272.685 kg/s. The blade tip speed ratio (TSR) is almost 6, with a tip speed of 30 m/s against a free-stream velocity of 5.3 m/s. A stagnation point forms in the −Y direction of the turbine — the maximum pressure zone — set by the combination of rotation and free-stream direction. The combined effect of the free-stream flow and the rotation-induced flow differs between the inner and outer blades: the pressure difference is smaller on the inner blades than on the outer ones, a result of the outer blades' higher linear velocity. By the end of this project, you'll be able to set up a transient Mesh Motion simulation of an H-type VAWT, define a rotating zone around the blades with the correct axis and speed, and interpret the velocity, pressure, TSR, and mass-flow results that characterize vertical-axis turbine aerodynamics.