DescriptionThis module uses ANSYS Fluent to simulate compressible flow through a 3D convergent-divergent nozzle, a fundamental problem in compressible flow modeling and high-speed propulsion applications. The simulation examines shock wave formation, Mach number evolution, and boundary layer behavior as flow accelerates from subsonic to supersonic conditions through the nozzle throat and divergent section.MethodologyThe nozzle geometry is analyzed under compressible flow conditions, resolving the transonic transition at the throat and the resulting supersonic flow field in the divergent section. Shock wave development is captured and visualized, along with its effects on pressure, temperature, and velocity. Boundary layer behavior along the nozzle walls is modeled under compressible conditions, including interactions between the boundary layer and shock waves, and flow separation regions in the divergent section are identified using CFD-based prediction methods.ConclusionResults include Mach number distributions showing the subsonic-to-supersonic transition, pressure and temperature profiles across shock regions (including deviations from ideal isentropic behavior due to friction and heat transfer), and flow separation zones affecting nozzle performance. Nozzle efficiency metrics such as thrust coefficient and specific impulse are calculated, and parametric studies support nozzle geometry optimization. These findings apply directly to rocket propulsion system design and supersonic wind tunnel development.

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

Fuel Injector, Three-Phase Flow (Mixture Model) — ANSYS Fluent CFD SimulationDescriptionWelcome to the Fuel Injector Three-Phase Flow CFD Simulation module. This project introduces fuel injection systems — a critical component in automotive and aerospace engineering — using the Mixture multiphase model in ANSYS Fluent to simulate three-phase flow inside an injector. Where the earlier injector case handled two phases, this one adds a third: liquid fuel, air, and fuel vapor all interact within the high-pressure injector, and the Mixture model represents their phase interactions, slip velocities, and mass transfer. Three-phase injector modeling of this kind supports automotive engines, aerospace propulsion, and combustion engineering. Within the Multiphase Flow: Beginner CFD Training Package, this project introduces the Mixture model and steps up to three phases, building on the two-phase VOF injector case.MethodologyThe project uses a pre-configured fuel injector geometry representing a real-world injector, including its internal passages and nozzle design, with a mesh built to capture the phase coupling within the complex geometry. Realistic boundary conditions are defined: flow rates, pressures, and phase fractions at the fuel inlet and air intake, along with nozzle-outlet and ambient conditions for spray formation. The Mixture model is central to the setup — the slip-velocity and mass-transfer models are selected and configured for accurate liquid–gas–vapor interaction and fuel vaporization, and turbulence and cavitation effects are incorporated, since these govern the multiphase behavior in the injector. The case is solved as a steady-state simulation.AnalysisPost-processing visualizes the phase distribution and velocity profiles through contours and vector plots that reveal how liquid fuel, air, and fuel vapor move through the injector and nozzle, with spray characteristics such as cone angle, droplet size distribution, and vapor concentration quantified in the near-nozzle region. From these results you can investigate how injection pressure affects spray atomization, how nozzle geometry influences the flow patterns, and how effectively fuel and air mix — identifying opportunities to optimize the injector design. These insights connect directly to improving engine efficiency, reducing emissions, and enhancing combustion stability through precise fuel delivery. By the end of this project, you'll be able to set up a three-phase injector simulation with the Mixture multiphase model, configure slip-velocity, mass-transfer, and cavitation effects, and interpret the phase-distribution, velocity, and spray results that characterize fuel injection.

Centrifugal Blower (MRF) — ANSYS Fluent CFD SimulationDescriptionWelcome to the Centrifugal Blower CFD Simulation module. This project explores the design and analysis of a centrifugal blower using ANSYS Fluent and the Multiple Reference Frame (MRF) approach. A centrifugal blower raises the pressure of a gas by flinging it outward with a rotating impeller and collecting it in a surrounding volute — a configuration found throughout HVAC systems, industrial ventilation, and dust-collection equipment. The challenge in simulating it is representing the spinning impeller alongside the stationary volute, which is exactly what the MRF method makes possible. As the opening project of the Rotary Equipment: Beginner CFD Training Package, it introduces the MRF approach in its simplest single-rotor form — the foundation for the rotating-machinery cases that follow.MethodologyThe core of the setup is the MRF approach for modeling rotating machinery, which divides the domain into a rotating zone around the impeller and a stationary zone for the volute. The rotating and stationary zones are defined and the interface between them is configured so the flow transitions smoothly from one to the other. The impeller is assigned its rotational speed, and appropriate boundary conditions are applied at the blower inlet and outlet. This arrangement captures the interaction between the impeller and the volute — including the flow near the volute tongue — while keeping the solution steady through the reference-frame approximation rather than physically rotating the mesh.AnalysisPost-processing focuses on the flow field within the blower. Three-dimensional velocity fields reveal the flow patterns and vortex structures developing within the rotating impeller, while pressure contours show the pressure recovery through the volute and the overall pressure rise the blower delivers. From these results you can evaluate the fundamental pressure–flow relationship, estimate the blower's efficiency, and study how the impeller and volute flows interact. The setup also supports exploring how rotational speed affects performance and generating performance curves across operating conditions. By the end of this project, you'll be able to set up a rotating-machinery simulation using the MRF method, define rotating and stationary zones and their interface, assign rotational speed, and interpret the velocity and pressure fields to evaluate centrifugal blower performance for HVAC and industrial ventilation applications.

Centrifugal Compressor — ANSYS Fluent CFD SimulationDescriptionWelcome to the Centrifugal Compressor CFD Simulation module. This project explores the design and analysis of a centrifugal compressor using ANSYS Fluent, examining the aerodynamics within one of the most important components in turbomachinery. A centrifugal compressor raises the pressure of a gas by accelerating it through a rotating impeller and then recovering that energy as pressure in a diffuser. Unlike a low-speed blower, a compressor operates at high speed where the gas density changes significantly, making it a compressible-flow problem with coupled pressure and temperature fields. Within the Rotary Equipment: Beginner CFD Training Package, this project introduces compressible flow in rotating machinery, stepping up from the incompressible blower and fan cases toward true high-speed turbomachinery.MethodologyBecause the flow is compressible, the setup solves the governing equations for compressible flow with a turbulence model suited to high-speed rotating flow. The rotation is handled with the Multiple Reference Frame (MRF) approach for steady-state analysis, dividing the domain into a rotating zone around the impeller and a stationary zone for the diffuser, with the interface between them configured for a smooth flow transition. The impeller is assigned its rotational speed, and the boundary conditions are set to represent the compressor's operating conditions. This arrangement captures the flow through the rotating impeller passages and the pressure recovery in the diffuser, resolving both the aerodynamic and thermodynamic behavior of the stage.AnalysisPost-processing focuses on the pressure and temperature fields that define compressor performance. Three-dimensional pressure contours reveal how pressure builds through the impeller and diffuser, while temperature contours show the thermodynamic response of the compressed gas. From these results you can compute the key performance metrics — the total-to-total pressure ratio and the isentropic efficiency — and study the flow through the impeller passages and diffuser. The setup also supports exploring how rotational speed affects performance across operating conditions. By the end of this project, you'll be able to set up a compressible rotating-machinery simulation using the MRF method, resolve the coupled pressure and temperature fields, and interpret the results to evaluate centrifugal compressor performance for aerospace propulsion and industrial process applications.

Multistage Compressor with 2 Rotors and 2 Stators — ANSYS Fluent CFD SimulationDescriptionThis project covers multistage compressor simulation using CFD, applying rotary-equipment and turbomachinery modeling principles to a compressor configuration with two rotor and two stator rows. In a multistage compressor, each rotor row adds energy to the flow and each stator row conditions it for the next stage, so the pressure rises progressively from stage to stage. Multistage compressors are widely used across mechanical engineering — in gas turbines, HVAC systems, and process industries — making this a foundational skill for turbomachinery-focused CFD work. Within the MRF: Beginner CFD Training Package, this project is the most complex of the compressor cases, extending the Moving Reference Frame method to multiple rotor and stator rows in series.MethodologyThe simulation setup covers configuring the rotating reference frames for the rotor stages, defining the interface conditions between the rotor and stator domains, and applying a turbulence model suited to compressor flow. Because each rotor row rotates while each stator row stays fixed, the Moving Reference Frame approach handles the rotation of the moving stages while the interfaces transfer the flow between successive rotor and stator domains. Boundary conditions specific to compressor operation are established, and the simulation is run with convergence monitored throughout the solution process.AnalysisThe analysis examines the flow patterns, pressure ratios, and temperature changes across the compressor stages, visualized through velocity fields, pressure distributions, and streamlines. From these results you can follow how the pressure builds progressively through the two rotor–stator stages and how each row shapes the flow entering the next. This understanding supports the analysis and optimization of compression systems such as gas turbine engines, industrial air compressors, and refrigeration systems. By the end of this project, you'll be able to set up a multistage compressor simulation with multiple rotating reference frames, define rotor–stator interfaces for staged flow, apply compressor boundary conditions, and interpret the pressure-ratio, velocity, and temperature results that characterize multistage compression — core skills for advanced turbomachinery work.

Twin Screw Pump — ANSYS Fluent CFD SimulationThis project analyzes the operation of a twin-screw pump using ANSYS Fluent. A twin-screw pump is a positive displacement device, transferring a fixed volume of fluid per cycle based on the rotational speed and pitch of its screws. As the two screws turn, they form enclosed chambers that move along the axial direction, creating a vacuum at the inlet and positive pressure at the outlet. This double-chamber arrangement allows the pump to handle fluids of both high and low viscosity with minimal pulsation.More specifically, the pump consists of two counter-rotating screw rotors that turn toward each other, trapping fluid in the space between their threads. As the screws rotate, this trapped volume progressively shrinks, compressing the fluid and driving it toward the outlet.In this study, the pump is used to handle a highly viscous fluid—glycerin. The rotation of the screws draws glycerin into the domain, increases its pressure, and pushes it toward the outlet.The geometry was designed in SolidWorks and refined in ANSYS Design Modeler, consisting of two rotating zones (the screw rotors) and one stationary zone (the pump housing). The model was meshed in ANSYS Meshing using an unstructured mesh, totaling 1,184,161 cells.MethodologyRather than applying rotation directly to the rotor geometry, the rotational motion is imposed on the surrounding fluid through a dedicated computational zone defined in the cell zone conditions. This is achieved using the Mesh Motion method, with a rotational velocity of 3 rad/s. Pressure boundary conditions are applied at the inlet and outlet, since fluid movement through the pump is driven entirely by pressure differences rather than forced flow.ResultsThe simulation produces 2D and 3D contours of velocity and pressure, along with streamlines around the rotors. The results show that fluid motion through the pump is governed by pressure gradients: rotor rotation generates suction at the inlet and pushes the fluid toward the outlet, with the streamlines clearly illustrating the rotational flow pattern inside the pump.

Plate Silencer and Sound Absorption — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of a plate silencer — a device used to absorb unwanted noise across industries from automotive and power generation to mining, subway tunnels, and architectural acoustics. A silencer works by vibrating in response to incoming sound waves; when the silencer's mode shapes match the sound waves, the energy is absorbed, quieting the environment. In this project, you'll model a symmetric silencer with a sinusoidal wavy plate at its center and study how acoustic waves behave as they travel through it, quantifying the silencer's noise-reduction efficiency. Within the Acoustics: Beginner CFD Training Package, this project applies the FW-H model taught earlier to a real noise-control device, opening the applied silencer and sound-absorption cases.MethodologyThe 2D symmetric silencer geometry, with a wavy central plate of 0.015 m wave amplitude, is designed in Design Modeler and meshed with a structured grid of roughly 17,000 elements for the acoustic domain. The Ffowcs-Williams & Hawkings (FW-H) acoustic model is set up, defining the far-field density (1.225 kg/m³), sound speed (340 m/s), and reference acoustic pressure (2×10⁻⁵ Pa), with acoustic sources defined near the inlet to introduce the pressure waves. The simulation must be transient to capture the wave behavior over time. The boundary conditions include a velocity inlet, a pressure outlet, and convective walls with a heat-transfer coefficient, and the setup uses the Realizable k-ε model with enhanced wall treatment and the energy equation.AnalysisPost-processing produces pressure, velocity, and temperature contours, along with Sound Pressure Level (dB) versus frequency at inlet and outlet receivers and — most importantly — the Transmission Loss diagram, which quantifies how much sound the silencer removes across the frequency range. From these results you can evaluate the silencer's noise-reduction efficiency and understand how the wavy plate absorbs acoustic energy. Noise control is a regulated requirement across the automotive, HVAC, power, and building industries, and the FW-H acoustic workflow built here is the foundation for designing mufflers, exhaust systems, and any noise-attenuating device. By the end of this project, you'll be able to set up a transient FW-H acoustic simulation of a silencer, define acoustic sources and receivers, and interpret the sound-pressure and transmission-loss results that measure noise-reduction performance.

Color Spraying on a Wall with Conical Injection — ANSYS Fluent CFD SimulationDescriptionThis project simulates color (paint) spraying onto a wall using a conical injection in ANSYS Fluent. The discrete phase is modeled with a one-way coupled DPM approach, in which the continuous phase influences the particles but the particles do not feed back on the flow. The injection is of the cone type, with a particle velocity of 10 m/s and a cone angle of 30 degrees.Geometry & MeshThe 3D geometry was created in SpaceClaim. The computational domain is 3 m long, 3 m wide, and 4 m high. The mesh was generated in ANSYS Meshing using an unstructured grid, with a total of 254,934 cells.Several assumptions underpin the simulation: the solver is pressure-based, the simulation is unsteady (time-dependent), and the effect of gravity is neglected.MethodologyThe problem setup is summarized below:Viscous model — laminarDiscrete phase — enabled, with unsteady particle tracking; the injected material is the color spray, the particle type is inert, and the injection type is a coneBoundary conditions — the side wall and back wall are stationary, with the discrete phase condition set to escape; the top wall is stationary, with the discrete phase condition set to trapSolution methods — SIMPLE pressure-velocity coupling; second-order discretization for pressure, second-order upwind for momentum, and first-order upwind for the modified turbulent viscosityInitialization — standard methodConclusionIn this simulation, the spray paint deposited on the wall is modeled using an injector that introduces the particles in a conical pattern. The cone angle governs the spread and range of motion of the particles, determining how they disperse from the nozzle and where they ultimately strike the wall — with the trap condition capturing the particles that reach the target surface and the escape condition allowing them to exit elsewhere in the domain.

DescriptionA slot is a deliberate gap built into a wing that splits the airfoil into two sections, allowing high-pressure air from below to feed energy into the flow over the upper surface. It's a classic aerodynamic device used to delay separation and boost lift — the same principle behind the leading-edge slots and slats on many aircraft wings. This project simulates the steady airflow over a slotted NACA 4421 airfoil in ANSYS Fluent to quantify exactly how that slot changes the wing's lift and drag.MethodologyThe geometry is built in two dimensions in Design Modeler, with the slot placed near the leading edge so the airfoil is divided into two distinct elements. The domain is meshed in ANSYS Meshing, producing a grid of roughly 260,000 cells resolved around the airfoil surface and through the slot region. The simulation runs as a steady, incompressible case. Air enters the domain at 10 m/s and the airfoil is held at a zero-degree angle of attack, isolating the effect of the slot itself from any change in incidence. Turbulence is handled with the standard k-ε model, and the solver is run to convergence to extract the aerodynamic force coefficients.AnalysisThe solution generates 2-D contours of pressure, velocity, and turbulent (eddy) viscosity. The pressure field clearly shows the stagnation point at the leading edge, where pressure rises sharply as the flow is brought to rest. The computed force coefficients for the slotted airfoil are a drag coefficient of 0.0755 and a lift coefficient of 0.3764. Compared with a plain NACA 4421 at the same zero angle of attack — reported at roughly Cd = 0.06 and Cl = 0.1 — both coefficients rise with the slot present. The lift gain is substantial, confirming the slot's intended job, while the modest drag increase shows the trade-off that comes with it. Together, these results illustrate how to set up a multi-element airfoil simulation, choose appropriate turbulence and solver settings, and extract and interpret lift and drag coefficients to evaluate an aerodynamic modification.