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.

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 focuses on the acoustic analysis of a six-bladed fan using ANSYS Fluent. The main objective is to study the airflow behavior and noise generation around the fan under specific operating conditions. The simulation aims to predict the broadband noise levels and to examine the distribution of the pressure and velocity fields, in order to understand the fan's combined aerodynamic and acoustic performance. This analysis helps identify the regions chiefly responsible for high noise generation and can be used to improve fan design for greater efficiency and reduced noise.Geometry & MeshThe fan geometry was created in ANSYS Design Modeler and consists of three zones representing the flow domain and the fan structure. The model features six blades attached to a central hub within a cylindrical enclosure. The geometry was imported into ANSYS Meshing, where a non-conformal, unstructured mesh was generated. A fine tetrahedral mesh was used to capture the complex flow features around the blades, resulting in approximately 3 million elements. The mesh quality was carefully checked to ensure accurate flow and acoustic predictions while maintaining computational efficiency.MethodologyThe simulation was performed in ANSYS Fluent using a pressure-based, steady-state solver. Turbulence was modeled with the standard k–ε model together with standard wall functions to account for near-wall behavior. The fan rotation was represented using the Multiple Reference Frame (MRF) approach at a rotational speed of 3000 RPM, and pressure inlet and pressure outlet boundary conditions were applied at the corresponding surfaces. The coupled algorithm handled the pressure-velocity coupling, and hybrid initialization was used to aid convergence. For the acoustic analysis, the Broadband Noise Sources model was employed to estimate the noise generated from the turbulent fluctuations in the flow.ConclusionThe results include contours of pressure, velocity, and acoustic power level across the fan domain. The pressure contours show higher-pressure regions near the leading edges of the blades and lower-pressure zones at the trailing edges, reflecting the lift effect produced by the rotation. The velocity contours reveal the maximum airspeed near the blade tips, demonstrating the strong tangential flow driven by the rotation. The acoustic power level plots indicate that the highest noise is concentrated around the blade tips and the outer casing, where the turbulent interactions and velocity gradients are most intense.Overall, the simulation successfully captures both the aerodynamic and acoustic behavior of the fan under steady operating conditions, showing how a broadband-noise acoustic model combined with the MRF approach can locate the dominant noise sources on a rotating fan and inform quieter, more efficient designs.

Ducted Fan: Noise and Thrust CFD Study, ANSYS FluentDescriptionThis project simulates a ducted fan installed within a room, investigating both its acoustic behavior and thrust performance. Airflow enters the room through a doorway at 0.5 m/s, while an outlet is positioned on the wall where the ducted fan is mounted, with the fan itself rotating at 1000 rpm.The 3D geometry was designed in Design Modeler, representing a 2×3 m rectangular room with a 2.5 m ceiling height and a 30 cm diameter fan. The domain was meshed in ANSYS Meshing, initially generating a tetrahedral mesh that was then converted to polyhedral elements to reduce element count and computational cost, totaling 699,432 elements.MethodologyGravitational acceleration was included in the negative Y-direction at 9.81 m/s², with the k-epsilon Realizable model employed to capture the expected wake structures and turbulence around the fan. A dedicated rotating zone was defined around the fan using the Moving Reference Frame (MRF) approach, while the Ffowcs Williams-Hawkings (FW-H) acoustic model was used to predict the resulting acoustic effects.ConclusionTwo sound receivers were placed within the room to evaluate the fan's noise impact — one positioned directly in front of the fan (Receiver 1), and another near the room's entrance by the door (Receiver 2). Flow contours show air entering the domain at 0.5 m/s, forming a wake around the fan zone before exiting the domain, with the duct itself acting as a natural silencer that limits how far the fan's sound propagates.As a result, while the sound pressure level remains high at Receiver 1 (closest to the fan), it drops to an acceptable range by Receiver 2, posing no concern for occupants near the entrance. This is confirmed by the A-weighted sound pressure level, which peaks at 80 dB — comfortably below the 120 dB threshold typically associated with harmful noise exposure. The simulation also reports a fan thrust force of 54.113455 N.

Acoustic in a Turbojet Intake Fan CFD SimulationDescriptionThis project simulates airflow inside a turbojet, examining the acoustic waves and sound generated within it using ANSYS Fluent. The incoming airflow is defined at a pressure of 85,416.92 Pa and a temperature of 283.9524 K, derived from the relevant governing equations.The model includes a turbojet fitted with a fan at its inlet, rotating at 2000 rpm about the X-axis. A dedicated airflow region surrounding the fan was defined and modeled using the Moving Reference Frame (MRF) approach to capture this rotational motion. The turbojet itself moves through the air at Mach 0.5 — since this exceeds the commonly used Mach 0.3 threshold for treating flow as compressible, the simulation accounts for compressibility accordingly, with a density-based solver applied and air density defined via the ideal gas law. The surrounding airflow domain was assigned a pressure far-field boundary condition at Mach 0.5.The 3D geometry was built in Design Modeler, consisting of the turbojet body with its internal fan positioned within a cylindrical computational domain representing the surrounding airflow. The region immediately around the fan was defined as an independent computational zone, allowing the fluid rotation induced by the fan to be captured through the frame motion method, while the full surrounding cylindrical domain carried the pressure far-field boundary condition. The domain was meshed in ANSYS Meshing using an unstructured grid totaling 3,723,166 elements.MethodologyAcoustic behavior was modeled using the Broadband Noise Sources model, with reference values set to match standard air properties: a reference density of 1.225 kg/m³, a reference sound speed of 340 m/s, and a reference acoustic power of 1×10⁻¹² W.ConclusionResults include contours and vector fields for velocity, pressure, temperature, Acoustic Power Level (dB), and Surface Acoustic Power Level (dB) throughout the domain, offering detailed insight into the turbojet's acoustic behavior. As air strikes the fan and its surrounding wall, the resulting acoustic parameters become most clearly defined in the region immediately downstream of the fan, with the Surface Acoustic Power Level concentrated along the fan surface itself — identifying it as the dominant noise source in this system.Plots of Acoustic Power Level and Surface Acoustic Power Level taken along the domain's centerline further clarify the precise magnitude and distribution of acoustic activity downstream of the fan, providing a clear quantitative picture of how the fan's rotation drives the turbojet's overall acoustic signature.

Jet Fan Application in a Tunnel Considering a Car Explosion, CFD Simulation ANSYS FluentDescriptionThis project simulates a car explosion within a tunnel using ANSYS Fluent, modeling a scenario where a car ignites due to a gasoline leak combined with airflow contact while crossing through the tunnel's interior. The resulting explosion ignites a fire and releases carbon dioxide into the enclosed tunnel space, where the gas accumulates and cannot disperse into open air, posing a serious hazard to other vehicles and passing pedestrians. To address this, tunnels are equipped with jet fans mounted on the roof, which draw carbon dioxide and other pollutants upward and expel them outward, serving as the primary defense against dangerous gas buildup during such an event.The 3D geometry was designed in SpaceClaim, representing the interior of a tunnel with a car modeled on the floor and a jet fan mounted on the roof. A specific volume at the car's rear was defined as the explosion source, alongside a designated region at the jet fan's inlet representing the fan itself. The domain was meshed in ANSYS Meshing using an unstructured grid totaling approximately 2,700,000 cells.MethodologyThis model assumes the combustion reaction has already occurred, so rather than modeling combustion itself, the simulation focuses solely on the resulting carbon dioxide emission. The Species Transport model was used to define the air and CO2 species, with airflow entering the tunnel at 300 K and 1.5 m/s. At the explosion source volume, a CO2 emission rate of 10,000 kg/m³·s and a thermal energy source of 1000 W/m³ were defined to represent the combustion byproducts. The jet fan itself was modeled using a fan boundary condition with a pressure jump of 1,000,000 Pa, which drives the surrounding air to be drawn into and expelled through the fan.Several assumptions were applied throughout: a pressure-based solver was used, the simulation was run under steady-state conditions, and gravitational effects were excluded.ConclusionResults include 2D and 3D contours of pressure, velocity, temperature, and the mass fractions of air and CO2. The results confirm that the jet fan system functions as intended — the explosion at the car's rear generates significant heat and releases CO2, which is then drawn upward and extracted through the jet fans, effectively preventing the gas from spreading throughout the tunnel's interior.To evaluate the jet fan's performance more rigorously, the simulation was repeated under identical conditions but with the fan boundary condition removed from the jet fan inlet. Without the jet fan operating, the results show CO2 filling the tunnel's interior unchecked, underscoring the jet fan system's critical role in maintaining a safe environment during a tunnel fire event.

Engine Room Ventilation System of a Ship — ANSYS Fluent CFD SimulationDescriptionThis project presents a complete CFD simulation of a ship's engine room ventilation system — one of the most critical thermal-management challenges in marine engineering. Engine rooms house compressors, pumps, fans, diesel engines, and electric motors, all packed into a confined space and all generating significant heat. Without proper ventilation, equipment overheats, efficiency drops, and safety risks rise. In this project, you'll use ANSYS Fluent to simulate how injected cool air at 300 K distributes through the engine room and removes heat from the operating machinery, allowing you to evaluate ventilation effectiveness and identify hot spots. As the opening project of the Marine Engineering: Beginner CFD Training Package, it introduces the CFD workflow through a self-contained internal-airflow problem in a familiar marine setting.MethodologyThe 3D engine room geometry is imported and prepared in SpaceClaim, then meshed in ANSYS Meshing with an unstructured grid of roughly 706,000 cells to resolve the complex internal flow domain and its multiple equipment volumes. The energy equation is activated to capture the heat transfer, and the machinery is modeled as distributed heat generators through volumetric heat sources defined in the cell-zone conditions — 12,500 W/m³ for the diesel engines and 8,333.33 W/m³ for the electric motors. The marine-specific boundary conditions comprise a mass-flow inlet supplying 35 kg/s of air at 300 K and dual pressure outlets for natural exhaust. Appropriate turbulence and solver settings are chosen for this internal forced-convection ventilation problem.AnalysisPost-processing produces temperature, velocity, and pressure contours, along with streamlines and velocity vectors that show how the cool air reaches the hot equipment surfaces. From these results you can evaluate ventilation effectiveness — identifying whether the cool air actually reaches the hottest machinery zones and where hot spots remain. The same CFD workflow built here — volumetric heat sources, forced ventilation, and internal recirculation — applies directly to engine rooms in submarines, ferries, cargo vessels, and offshore platforms, as well as to data centers and industrial machinery enclosures on land. By the end of this project, you'll be able to set up an internal forced-convection ventilation simulation, model machinery as volumetric heat sources, and interpret the flow and temperature fields to assess how effectively a confined marine space is cooled.

Generator Room Ventilation Applying Fans, ANSYS Fluent CFD Simulation TutorialDescriptionThis project simulates ventilation within an industrial generator room using ANSYS Fluent. Generators are among the most widely used and essential electricity sources across various industries, but they generate substantial heat — enough that when several units operate together, thermal comfort suffers significantly, and operators may struggle to approach the generators safely in summer due to extreme heat buildup. To address this, fans are placed within the generator room to bring indoor temperatures down to a level suitable for operators.The 3D geometry was designed in SpaceClaim, representing a rectangular space housing 32 diesel generators. The domain was meshed in ANSYS Meshing, totaling 3,854,957 elements.MethodologyThis project simulates the generator room's heating, ventilation, and air conditioning (HVAC) performance across three progressive configurations. The room was first simulated without any fans, establishing a baseline temperature reading. Thirty-two fans rated at 11,000 CFM were then introduced, considerably reducing the temperature. To further improve ventilation and achieve the desired thermal comfort between generator rows, an expanded configuration adding fans rated at 36,500 CFM was also evaluated.Turbulence was resolved using the Realizable k-epsilon model, with the energy equation enabled to capture temperature variation throughout the generator room across each configuration.ConclusionThe baseline simulation, run without any fans, showed temperatures between the generators exceeding 49°C — confirming the clear need for active cooling. Introducing 32 fans at 11,000 CFM each brought this temperature down considerably, to 36°C, demonstrating a meaningful but still incomplete improvement.A further configuration using 64 fans total (32 at 11,000 CFM and 32 at 13,500 CFM) was then evaluated to push thermal comfort closer to the desired target. This final configuration showed markedly improved airflow velocity throughout the room compared to the previous setup, with the temperature between the generators dropping all the way to match the outside ambient temperature of 30°C — confirming that this expanded fan configuration successfully achieves the thermal comfort objective for generator room operators.

ACSC Performance with Diffuser Orifice Plate, Paper Numerical Validation, ANSYS Fluent CFD Simulation TutorialDescriptionThis project simulates an air-cooled steam condenser (ACSC) system within a 600 MW power plant, based on the reference article "Effects of a diffuser orifice plate on the performance of air-cooled steam condenser," with results compared and validated against the paper's published data using ANSYS Fluent.ACSC systems are designed primarily to prevent energy waste in power plants — they condense hot steam exiting the turbine and transfer the resulting water from the distillation process back to the steam turbine's pump section. The power plant modeled in this study consists of seven rows of ACSC systems, with this simulation focusing specifically on the fourth row. Each row contains eight fans, with each fan positioned beneath two diagonally oriented porous plates. During operation, hot, low-pressure steam exiting the turbine passes through a series of pipes and is transferred into the interior space bounded by the diagonal plates installed on either side of each pipe.The 3D geometry was built using SolidWorks and Design Modeler, representing the cooling system's eight rows of hot steam pipes, the diagonal porous plates flanking each pipe, and the eight fans mounted on a single platform. The domain was meshed in ANSYS Meshing using a hybrid mesh totaling 2,668,772 elements.MethodologySince the core objective involves the distillation process, a constant steam saturation temperature of 319.75 K was defined, reflecting that condensation occurs at saturation temperature under constant pressure. Each of the eight fans was modeled using the fan boundary condition, which requires specifying a pressure jump to represent the pressure difference generated across the fan along its defined direction. This pressure jump was defined through a polynomial function relating it to the axial velocity passing through the fan surface, imported directly into the fan boundary condition setup.ConclusionResults include 3D contours of velocity, pressure, and temperature. The temperature contour confirms that ambient air absorbs heat from the steam pipes, driving the condensation process as intended.A graph of volumetric effectiveness versus fan number was also extracted and validated against Figure 5-c of the reference article. The study's central objective was to examine how ambient airflow velocity affects the system's fan performance in terms of volumetric transfer from the cooling airflow. To quantify this, a dimensionless parameter — volumetric effectiveness — was defined as the ratio between the volumetric flow rate delivered by the fans in the numerical solution and the ideal volumetric flow rate of 428 m³/s. Comparing this result against the reference paper's data showed acceptable solution accuracy with low error, confirming the simulation faithfully reproduces the reference system's performance behavior.

Radiator Thermal Performance with Fans, Paper Numerical Validation, ANSYS Fluent TutorialDescriptionThis project examines heat transfer and airflow behavior around a radiator, based on the reference article "CFD Study on Thermal Performance of Radiators in a Power Transformer: Effect of Blowing Direction and Offset of Fans," with results compared and validated against the paper's published data using ANSYS Fluent.The radiator features three fans driving horizontal airflow, along with several rows of fins and aluminum plates designed to enhance heat transfer. The 3D geometry was built in Design Modeler, consisting of three main components: the radiator body, the fans, and the surrounding air domain. The radiator itself is divided into four sections, each containing fourteen rows of plate fins along with hot water transfer pipes running along the top and bottom.Three fans are positioned along the left side of the radiator body, generating horizontal airflow across its surface. The domain was meshed in ANSYS Meshing using an unstructured grid, with inflation boundary layer mesh applied along the radiator wall surfaces to properly resolve heat transfer between the fins and surrounding airflow, and face sizing applied to the fin surfaces for additional mesh refinement. The total element count reached 4,683,472.MethodologyHot water flows through the radiator's upper and lower pipes and its internal fins, with all pipe and fin wall surfaces assigned temperature values that vary with height along the radiator plates. This temperature profile was implemented through a temperature boundary condition driven by a UDF: hot water enters the radiator's upper section at 366.15 K and, as it flows downward through the pipes while exchanging heat with the surrounding airflow, cools to a minimum of 353.15 K by the lower section. Since this temperature variation follows primarily from the vertical flow direction, the UDF defines it as a simple linear profile: 346.15+5*y.The three fans were modeled using the fan boundary condition, positioned along the plates on the radiator's side. Since incoming flow to these fans runs horizontally, rotational speed was defined about the x-axis. Since the fan boundary condition defaults to suction-mode flow but this model required blowing instead, the Reverse Fan Direction option was activated to correctly orient the airflow. Each fan's pressure jump was defined using a polynomial pressure-velocity function with coefficients of 80 and -10.ConclusionThe net heat loss rate from the radiator plates to the surrounding airflow was calculated and compared against the reference paper's results, using Figure 5 of the article under the ONAF mode (forced convection heat transfer). Since the rate of heat loss from the radiator body to its surroundings can be equated to the temperature difference between inlet and outlet airflow, this comparison was performed using the Report tool's Total Heat Transfer Rate option under Flux Reports, yielding a value of 3738 (units consistent with the reference comparison) that aligned well with the paper's reported results.Additional 2D and 3D contours of temperature, velocity, and pressure were also obtained, along with 3D pathlines and velocity vectors, providing a comprehensive view of the flow and thermal behavior throughout the radiator assembly.