Shock Wave in a Supersonic Airflow with Transient Solver, ANSYS Fluent CFD Simulation TrainingDescriptionThis project simulates supersonic airflow encountering a two-way oblique airfoil barrier passing through a channel, investigating the resulting fluid behavior and the formation of a shock wave phenomenon using ANSYS Fluent.The airflow surrounding the obstacles and channel is set at a temperature of 129.46 K and a Mach number of 2.49, with flow direction assumed generally uniform. Mach number — a non-dimensional ratio of fluid velocity to the local speed of sound — is a critical parameter whenever flow velocity approaches or exceeds the speed of sound, with aerospace applications representing one of its most significant use cases. The 3D geometry was designed in Design Modeler and meshed in ANSYS Meshing using an unstructured mesh totaling 4,466,857 elements.MethodologyA Density-Based solver was used to capture the compressible nature of the flow, appropriate given the high Mach number and strongly compressible behavior characteristic of shock phenomena. The simulation was run under unsteady (transient) conditions to capture the shock formation process over time.ConclusionResults include 2D and 3D contours of pressure, temperature, velocity, density, and Mach number, along with 2D and 3D pathlines — all extracted at the final second of the unsteady simulation. The results confirm well-formed shock structures, occurring where the flow collides with the sharp points of the geometry, producing abrupt changes in Mach number. Pressure variations are clearly evident throughout the shock formation regions in the resulting contours.

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.

Inviscid Supersonic Flow Over F-16 Aircraft SimulationDescriptionThis 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. Assuming inviscid flow 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.

F-22 Aircraft CFD Simulation, ANSYS FluentDescriptionThis project simulates an F-22 aircraft using ANSYS Fluent. The geometry was designed in SpaceClaim and meshed using Fluent Meshing, generating approximately 5 million polyhedral elements. Given the high Mach number of 0.4, the simulation was carried out using the density-based solver, with the flow assumed to be steady.A related wing lift-to-drag ratio optimization of this aircraft using RBF Morph is also available and can be viewed here.MethodologyThe aircraft surface was defined as a wall, with all remaining boundaries set as pressure far-field conditions at a Mach number of 2. The SIMPLE algorithm was used with an explicit formulation, standard initialization, and the k-ε Realizable turbulence model. The working fluid was treated as an ideal gas (air).ConclusionThe simulation produced a drag force of 74.067622 kN. Since the model was solved using symmetry, doubling this value yields approximately 148,135.244 N (≈148 kN) — close to the F-22's known engine thrust of roughly 156 kN, confirming a relatively accurate simulation with a percentage error of:Percentage Error = (|156,000 − 148,135.244| / 156,000) × 100% ≈ 5.04%The velocity contour shows the distribution of velocity magnitude around the aircraft, with higher velocities concentrated near the wings and tail. The pressure contour reveals higher-pressure regions at the wing leading edges and nose, with lower-pressure regions along the upper wing and tail surfaces. A pressure coefficient plot, taken on a plane 5 meters from the aircraft's center, illustrates the relative pressure distribution across that plane — positive values indicating high-pressure regions and negative values indicating low-pressure regions relative to freestream conditions.Overall, the close agreement between the simulated drag force and the F-22's actual engine thrust — within roughly 5% error — confirms the simulation's accuracy, and the resulting velocity, pressure, and pressure coefficient contours provide a clear picture of flow behavior around the aircraft, suitable for further design analysis and optimization work.

Supersonic Jet Ramped Intake Simulation, ANSYS Fluent CFD TrainingDescriptionThis project simulates a supersonic jet ramped intake using ANSYS Fluent. With the development of jet engines and the resulting ability of aircraft to travel at supersonic speeds, engineers faced the challenge of designing intakes capable of supplying the airflow required by the engine across a wide operating envelope, while delivering high-pressure recovery and low flow distortion.These design demands grew significantly more complex as aircraft speeds increased toward Mach 3.0 and Mach 3.2 — the design points for the XB-70 and SR-71, respectively. The intake forms part of either the fuselage or the engine nacelle.Ramped, or angled, intakes are specifically designed so that their angled surfaces generate shock waves, allowing uniform, undisturbed flow to enter the channel and reach the engine. The cross-sectional geometry changes progressively along the channel to shape the flow accordingly.This project models a ramped intake based on the geometry of the F-15 intake, placed within a supersonic flow at Mach 1.4, examining the resulting changes in velocity, pressure, and velocity profile along the channel.The 3D geometry was designed in Design Modeler, with the domain including a velocity inlet, pressure outlet, wall boundaries for the intake surface, and far-field boundaries along the sides. The model was meshed in ANSYS Meshing using an unstructured grid totaling 1,278,343 elements.MethodologyThe simulation used a density-based solver, with turbulence modeled using the k-omega SST model. The intake was simulated at its operational design point, with an inflow velocity of Mach 1.4.ConclusionThe Mach number contour clearly reveals the formation of oblique shock waves and expansion fans both at the intake entrance and within the intake channel. These shock waves decelerate the flow to subsonic speeds near the inlet and promote flow uniformity, while the channel itself behaves similarly to a converging-diverging nozzle — an effect also reflected in the pressure and temperature contour results.Velocity contours across different regions of the intake further illustrate how the channel's wall geometry progressively uniformizes the flow speed along its length. The pressure contour along the intake shows a characteristic pressure drop at the opening, followed by gradual recovery through the channel — a behavior that keeps the engine operating under ideal conditions and helps prevent compressor stall.

Rampressor, ANSYS Fluent CFD Simulation TrainingDescriptionThis project simulates air compression inside a Rampressor using ANSYS Fluent — a distinctive type of supersonic compressor rotor capable of achieving high pressure ratios through ramjet-style supersonic shock wave compression.The operating principle relies on gas flow passing between a fixed outer housing and an angled inner surface, or "ramp." As this inner ramp surface rotates relative to the fixed outer body, it progressively narrows or widens the gas passage. This changing cross-section triggers shock wave formation and alters the local Mach number, ultimately compressing the gas.In this simulation, the Rampressor's inner wall rotates about its central (z) axis at 40,000 rpm, modeled using the frame motion technique: the shroud wall itself is assigned zero rotational velocity, while the surrounding computational region containing the rotating ramp is assigned the full 40,000 rpm rotational speed within the frame motion setup. Given the compressive nature of the device, pressure boundary conditions were applied at the inlet and outlet, set to relative pressures of 104,600 Pa and 350,000 Pa respectively. Since the internal airflow is fully compressible, a density-based solver was used throughout.Geometry & MeshThe 3D geometry was designed in Design Modeler as a three-dimensional ring structure, with the sides defined as inlet and outlet sections. The outer wall was defined as static, while the inner wall — featuring several angled ramp surfaces — was defined as rotating.The domain was meshed in ANSYS Meshing using an unstructured grid totaling 1,785,931 elements.MethodologySeveral assumptions were applied to the simulation: a density-based solver was used, the flow was treated as steady-state, and gravitational effects were excluded.Key simulation settings included:Viscous model: Standard k-epsilon with standard wall functions; energy equation enabledBoundary conditions: Pressure inlet at 104,600 Pa gauge total pressure and 300 K total temperature; pressure outlet at 350,000 Pa gauge pressure; shroud and inner wall defined as rotating walls with 0 rpm assigned directly to the wall motion (rotation handled via the frame motion region) and zero heat fluxSolution methods: Implicit formulation, with first-order upwind schemes applied to flow, turbulent kinetic energy, and turbulent dissipation rateInitialization: Hybrid methodConclusionResults include 2D and 3D contours of pressure, velocity, density, temperature, and Mach number. The results show a clear pressure increase at the Rampressor outlet, along with elevated Mach numbers in the gap between the ramp surfaces and the surrounding equipment body — consistent with the shock-compression mechanism driving this device's operation.

DescriptionThis project simulates airflow through an axial flow compressor, specifically NASA Rotor 37, using ANSYS Fluent. To keep the model tractable, only a single row of rotating blades on the central rotor is represented rather than the full multi-stage compressor assembly. The blades rotate at 14043 rpm, with an air mass flow rate of 33.25 kg/s through the compressor, and the goal is to characterize how the airflow behaves and how pressure builds around the blades as the air is compressed. The 3D geometry is built in SOLIDWORKS and imported into Design Modeler, then meshed in ANSYS Meshing with an unstructured grid of 278,162 elements.MethodologyGiven the compressibility of the flow, the density-based solver is used. Rotor motion is handled through the Frame Motion technique: the blades themselves are treated as stationary, while the surrounding fluid domain is given a rotational speed equal to the rotor's, effectively reversing which frame moves so the flow field around the blades can be resolved in a rotating reference frame. Correspondingly, the compressor blade walls are set as moving walls with zero rotational speed relative to that rotating frame, keeping the blade surface consistent with the "stationary blade" assumption.AnalysisThe results include both 2D and 3D contours of pressure, temperature, velocity, and density, along with path lines and velocity vectors describing the flow around the blades. The 2D contours and path lines are extracted on a YZ plane perpendicular to the compressor axis, cutting through the mid-span of the blade passage, giving a clear view of how the flow develops as it moves through the blade row. Pressure, temperature, and heat transfer coefficient distributions are also reported directly on the blade surfaces, characterizing the thermal and aerodynamic loading the blades experience during compression.

Vortex Tube CFD Simulation, ANSYS Fluent TrainingDescriptionA vortex tube is a mechanical-thermal device that splits a compressed air flow (or any inert gas) into separate hot and cold streams. Its standard components include one or more inlet nozzles, a hot end tube, a vortex chamber, a cold orifice, and a control valve or plug positioned at the hot end, with exits configured on either or both sides.This project simulates a vortex tube using ANSYS Fluent. Air enters the domain at a static pressure of 7 bar and a total temperature of 300 K, then begins rotating within the tube in a high-speed vortex motion. This rotating gas naturally separates into hot and cold streams, driven by differences in angular momentum between individual gas particles — the hot airflow exits through the outlet chamber, while the cold airflow returns and exits through the opposite (left) side.The geometry was built in SpaceClaim, with a polyhedral mesh generated using Fluent Meshing, totaling 497,635 elements.MethodologyA density-based solver was used to model the airflow, with air density defined using the ideal gas law and viscosity modeled via Sutherland's law. Turbulence was captured using the Spalart-Allmaras model.ConclusionThe results include temperature, pressure, and velocity contours throughout the vortex tube. Flow vectors clearly illustrate the air's rotational motion, showing how lower-momentum air is redirected back toward the cold outlet, while pressure, temperature, and density variations are also evident across the domain.The simulation confirms the expected vortex tube behavior: the cold outlet registers a temperature below the inlet condition, while the hot outlet registers a temperature above it. The mass-weighted average total temperatures at each boundary were:LocationTotal Temperature (K)Inlet300Cold outlet287.25Hot outlet353.02

Hypersonic Combustion in Scramjet with Viscous Heating, CFD Simulation ANSYS Fluent TrainingDescriptionHydrogen combustion inside a scramjet engine at hypersonic speed represents one of the most demanding reacting-flow problems in CFD, coupling supersonic compressible flow, finite-rate chemistry, and wall heating within a single transient case.A scramjet (supersonic-combustion ramjet) has no moving parts — it relies entirely on engine geometry to compress incoming air, inject and burn fuel, and expand the combustion products for thrust. This distinguishes it from a conventional ramjet, which decelerates flow to subsonic conditions before combustion occurs; a scramjet instead sustains supersonic combustion throughout, enabling flight above Mach 5.The 2D geometry consists of two sections — a lower preheating region and an upper stable-burn region — built in Design Modeler and meshed in ANSYS Meshing using a structured grid of 16,320 cells. Inlet air enters at Mach 6, with the domain initialized at 300 K. At the mid-nozzle location, where the flow decelerates to Mach 1, hydrogen is injected supersonically, triggering combustion within the nozzle.MethodologyCombustion is modeled using the Species Transport model with its volumetric reaction sub-model, with air treated as an ideal gas so that density responds correctly to the steep temperature rise generated during burning. Turbulence is captured using the standard k-ε model, and the case is solved as transient to resolve the developing flow field and flame structure.Given the numerically stiff nature of hypersonic reacting flows, first-order discretization schemes and reduced under-relaxation factors are deliberately applied to maintain stable convergence throughout the solution process.ConclusionResults include 2D contours and vector fields for pressure, temperature, velocity, Mach number, density, and turbulence intensity. The flow physics follows a clear progression: air enters the domain, decelerates to Mach 1 at the combustion section, then re-accelerates toward the outlet. Combustion drives temperatures beyond 4000 K, with viscous heating clearly visible in the near-wall elements, where high-speed shear converts kinetic energy into heat at the wall surface.

F1 Aerodynamics CFD Simulation, Pressure-Based and Density-BasedDescriptionThis project examines the aerodynamic coefficients of a Formula One (F1) car using two distinct solver approaches — pressure-based and density-based — at a speed of 111 m/s with zero lateral angle (representing straight-line travel).At ground level, this velocity corresponds to a Mach number of approximately 0.32, placing the flow within the transition zone between incompressible and compressible behavior. Given this borderline regime, the drag coefficient was investigated using both solver types to compare their performance and accuracy on this geometry.Since flow characteristics also influence the upstream region in subsonic flow, the computational domain was sized generously upstream. Downstream, the domain was similarly extended to properly capture the wake vortices shed behind the geometry, supporting convergence in the larger computational domain.The geometry was modeled in Design Modeler, with elements generated in ANSYS Meshing using a polyhedral mesh totaling 1,253,296 elements.MethodologyThe problem was solved under steady-state conditions using both pressure-based and density-based solvers, with turbulence modeled using the Realizable k-epsilon model in both cases.ConclusionConvergence was assessed by monitoring the iterative solution and confirming residuals reached the defined convergence criteria, with particular attention paid to the convergence behavior of drag force — a stable, non-fluctuating value in this quantity indicating a converged numerical solution.SolverDrag Force (N)Iterations to ConvergePressure-based-4872.6194200Density-based-5542.2328350The drag force results are broadly comparable between the two solver types, indicating that for this Mach number and geometry, the density-based solver's compressible-flow handling did not introduce dramatically different results. The key distinction lies in computational efficiency: the pressure-based solver converged in fewer iterations, making it more time-efficient.Given its lower computational cost alongside reasonably accurate results compared to the density-based approach, the pressure-based solver is identified as the more appropriate choice for this particular simulation case.