Kaplan Turbine CFD Simulation, ANSYS Fluent TrainingDescriptionThis project simulates a Kaplan turbine using ANSYS Fluent. Turbomachines, also known as fluid machines, are widely used across industry, making it essential to understand their behavior in a fluid environment. Turbomachines generally fall into two categories: the first group — such as fans and compressors — takes energy and transfers it to the fluid, while the second group extracts energy from the fluid and transfers it to the system, as seen in wind and water turbines. Kaplan turbines belong to this second category.Kaplan turbines are a type of inward-flow reaction turbine, among the most widely used turbine designs in industry, operating through a combination of axial and radial flow concepts. Water enters through an inlet tube that rotates around guide vanes, flowing tangentially through these vanes before being redirected into a spiral pattern by the runner's propeller blades — ultimately driving the runner's rotation.This project investigates water flow passing through a Kaplan turbine rotating at 3300 rpm. The geometry was designed in Design Modeler and meshed in ANSYS Meshing using an unstructured grid totaling 919,824 cells.MethodologyTurbine rotation was modeled using the MRF (Moving Reference Frame) approach, applied through the Frame Motion option. Rather than rotating the turbine blades themselves, the surrounding fluid is treated as rotating at a velocity matching the turbine's own rotational speed, implemented through the MRF tool within Cell Zone Conditions.ConclusionResults include 2D and 3D contours of pressure, velocity, and surface pressure, along with velocity vector fields illustrating the fluid's rotational motion around the turbine blades.The surface pressure contour reveals localized regions on the turbine blades experiencing notably reduced pressure — these areas represent potential sites where cavitation could occur, and warrant closer examination in subsequent, more detailed analysis to assess cavitation risk and its potential impact on turbine performance and blade integrity.

Kaplan Hydro Turbine Evaluation, ANSYS Fluent CFD Simulation TutorialDescriptionThis project evaluates a Kaplan hydro turbine using ANSYS Fluent. The Kaplan turbine is a propeller-type water turbine featuring adjustable blades, classified as an inward-flow reaction turbine — meaning the working fluid undergoes a pressure change as it passes through the turbine, giving up its energy in the process. Power is recovered from both the hydrostatic head and the kinetic energy of the flowing water, with the Kaplan design combining characteristics of both radial and axial turbines.This project studies the turbine's hydrodynamic behavior, with the rotor set to an angular velocity of 16.5 rpm. Boundary conditions include a constant mass flow rate of 1000 kg/s at the inlet, zero gauge pressure at the outlet, and symmetry conditions applied to all side walls, given their distance from the region of primary interest. The study also evaluates turbine performance through the resulting drag force.The geometry — a small-scale Kaplan turbine — was designed in Design Modeler and meshed in ANSYS Meshing using an unstructured grid totaling 9,861,922 cells.MethodologyTurbine rotation was modeled using the MRF (Moving Reference Frame) approach via the Frame Motion option, treating the fluid surrounding the turbine blades as rotating rather than the blades themselves. Given the turbomachinery nature of this simulation, a dedicated cylindrical zone was separated from the broader computational domain, with the fluid within this zone assigned a rotational velocity matching the turbine's own, implemented through the MRF tool within Cell Zone Conditions.ConclusionResults include 2D and 3D contours of pressure, velocity, and surface pressure, along with velocity vectors and streamlines illustrating the fluid's rotational motion around the turbine blades.The lowest pressure occurs at the turbine's leading edge, consistent with the highest velocity values occurring at the blade tip. Velocity contours further show that rotational velocity — and the influence of the associated source terms — increases with distance from the turbine axis. The pressure distribution along the turbine walls forms two distinct regions: a high-pressure zone upstream, before the flow interacts with the turbine, and a corresponding low-pressure zone downstream, behind the turbine geometry.The flow vectors also capture the wake region's resolved behavior — a central challenge in aerodynamic simulation of this kind — revealing a suction mechanism active at the turbine's lower sections and a blowing mechanism at the upper sections. A core vortex adjacent to the turbine body is likewise captured, offering insight into how the flow field is reshaped in close proximity to the rotating walls.

DescriptionThis project uses ANSYS Fluent to simulate a Darrieus-type vertical axis water turbine (VAWT) submerged in flowing water, applying the Dynamic Mesh method to capture rotation driven by the surrounding flow — a relevant application in marine renewable energy and hydrokinetic power generation. Unlike wind-based VAWTs, this turbine extracts kinetic energy directly from water flow, with its rotational axis perpendicular to the flow direction. The three-bladed turbine rotates freely in response to the fluid forces acting on it, allowing its performance under water flow conditions to be evaluated.MethodologyThe 3D geometry is built in DesignModeler, consisting of a large computational domain containing a three-bladed Darrieus turbine (0.5 m blade height), with the turbine center positioned 3 m from the inlet, 10 m from the outlet, and 0.75 m from the top and bottom domain surfaces. The domain is meshed in ANSYS Meshing using a hybrid grid — unstructured around the turbine body and structured elsewhere — totaling 7,422,668 elements.Water enters the domain at 1 m/s along the horizontal axis, with a pressure outlet at atmospheric conditions and symmetry conditions applied to the top and lateral surfaces. The turbine's rotation is captured using the Dynamic Mesh model, with a cylindrical sub-region isolating the turbine blades as rigid bodies. Rotational motion is defined with one degree of freedom (1-DOF), using a blade mass of 1 kg and moment of inertia of 3.09 kg·m². The simulation is run transient, over 50 seconds with a 0.05 second time step, consistent with the dynamic mesh approach.ConclusionResults include 2D contours of velocity, pressure, and turbulent kinetic energy, along with pathlines and velocity vectors on a plane through the turbine center. Turbine torque and other performance characteristics are also analyzed, providing insight into the turbine's power extraction behavior — relevant to marine hydrokinetic energy system design and evaluation.

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

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

DescriptionThis project simulates a floating solar panel system, a photovoltaic installation deployed on a water surface rather than on land, using ANSYS Fluent. Floating this way brings several advantages over conventional ground-mounted panels: the water's cooling effect improves energy output, land use is freed up for other purposes, and the panel coverage helps reduce evaporation and limit algae growth on the water body beneath it. The simulation is fully 3D, capturing the panel floating on the water surface as it responds to the surrounding air and water phases. The geometry, comprising the water tank and floating panel, is built in SpaceClaim and meshed in ANSYS Meshing with a grid of 479,895 cells.MethodologyWater and air are modeled as two interacting phases using the Volume of Fluid (VOF) multiphase model, capturing the free surface the panel floats on. Because the panel needs to move and settle naturally under buoyancy, a 6-degree-of-freedom dynamic mesh is used, allowing the panel to float freely, with remeshing and smoothing keeping the mesh valid as it moves. Radiation is also activated, using the Discrete Ordinates model, to capture how sunlight reaches and heats the panel surface.AnalysisThe volume fraction contour shows a clean, stable interface between air and water, indicating the panel maintains steady buoyancy without disruptive interface instabilities that could otherwise compromise its floating stability and energy generation. The incident radiation contour shows a largely uniform distribution of sunlight across the panel surface, supporting consistent energy output, while the temperature distribution shows a stable thermal profile with no significant hotspots, suggesting the design avoids the localized heating that would otherwise degrade efficiency or panel materials over time. Together, these results indicate the floating panel system performs reliably in its intended floating, sun-exposed environment.

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.

Transformer Room Ventilation CFD Simulation, ANSYS Fluent TrainingDescriptionThis project simulates air conditioning within a transformer room using ANSYS Fluent. Transformers transfer electrical energy between two or more windings through electromagnetic induction, and for safety reasons, they're typically housed in dedicated rooms requiring an optimized air conditioning system to manage the substantial heat these units generate as they operate.The 3D geometry was designed in Design Modeler, representing a two-part room separated by a thin membrane wall. The room features 10 air inlet ducts positioned along the top and 4 outlet ducts along the side walls, with 3 transformers modeled as internal heat sources. A porous medium representing a louver window was applied at each airflow outlet. The domain was meshed in ANSYS Meshing, totaling 592,411 elements.MethodologyThe room's central divider was modeled as a wooden wall with a thermal conductivity of 0.173 W/m·K. The three transformers were modeled as aluminum components (thermal conductivity of 202.4 W/m·K), each generating a constant heat source of 6060.606 W/m³.Airflow enters the room through ducts positioned atop one of the transformer room walls, at velocities of 1.531 m/s and 2.04 m/s, angled at 45 degrees, and entering at 303.15 K; it exits through outlets held at atmospheric pressure. To improve the distribution of hot exhaust air leaving the room, louver windows were incorporated at the exhaust ducts, modeled as a porous zone with a porosity coefficient of 0.6 and a viscous resistance (inverse permeability) of 211,100,000 1/m².Convective heat transfer was also applied around the transformer walls, assuming a fluid bulk temperature of 300 K and a heat transfer coefficient of 24 W/m²·K. Turbulence was resolved using the standard k-epsilon model, with the energy equation enabled to capture temperature variation throughout the domain.ConclusionResults include 2D contours of pressure, temperature, and velocity throughout the transformer room. The temperature contour confirms that forced convection and the resulting airflow motion within the room effectively lower the overall temperature — demonstrating that the combined ventilation and louver-assisted exhaust design successfully manages the heat generated by the transformers, keeping the room within a safer operating temperature range.

Electric Field Effect on Nanofluid Heat Transfer (EHD) — ANSYS Fluent CFD Simulation TrainingThis project investigates the flow of a nanofluid through a bumpy channel under the influence of an applied electric field, using ANSYS Fluent. The flow is treated as steady-state and modeled using a single-phase approach, with the nanofluid's thermophysical properties—density, viscosity, specific heat, thermal conductivity, and electrical conductivity—adjusted to reflect the presence of the nanoparticles. The applied electric field alters the fluid's flow behavior, which in turn enhances heat transfer. The surface-averaged temperature of the nanofluid is 300 K at the inlet and 301.926 K at the outlet.Geometry and MeshThe fluid domain geometry was created in Design Modeler, and the computational mesh was generated in ANSYS Meshing. The mesh is unstructured, with a total of 17,640 elements.Setup and AssumptionsThe simulation uses a pressure-based solver under steady-state conditions, with gravity effects neglected. The energy equation is active, and turbulence is modeled using the realizable k-epsilon model with standard wall functions.The fluid is defined as a modified water-based nanofluid with a density of 998.2 kg/m³, specific heat of 4182 J/kg·K, thermal conductivity of 0.6 W/m·K, viscosity of 0.001003 kg/m·s, constant UDS diffusivity, electrical conductivity of 1,000,000 S/m, and a magnetic permeability of 1.257×10⁻⁶.At the inlet, a velocity inlet condition is applied with a velocity magnitude of 1 m/s, turbulence intensity of 5%, turbulent viscosity ratio of 10, and a temperature of 300 K. The outer solid wall is held at a fixed temperature of 340 K.The SIMPLE scheme handles pressure-velocity coupling, with least-squares cell-based gradients. Pressure and energy are discretized using second-order schemes, momentum uses second-order upwind, and turbulent kinetic energy and dissipation rate use first-order upwind. Hybrid initialization is used to start the solution.Results and DiscussionWith the electric field applied, the average outlet temperature of the nanofluid reaches 301.926 K, compared to 300 K at the inlet, corresponding to a heat flux of 72,474.1 W. Without the electric field, the outlet temperature drops slightly to 301.92 K.Comparing the two cases highlights the effect of the electric field: its application raises the outlet temperature by approximately 0.04 K and increases the heat transfer rate to the nanofluid by about 54 W/m².

Magnetic Field Effect on Nanofluid in a 2D ChannelDescriptionThis project simulates the effect of a magnetic field on a nanofluid in a two-dimensional channel using ANSYS Fluent software. The problem is carried out and investigated through CFD analysis.The present model is designed in two dimensions using Design Modeler software. Because of its symmetrical geometry, the model is drawn as a two-dimensional channel. It has a length of 0.49 m and a width of 0.01 m, with an inlet boundary on the left and an outlet boundary on the right. The lower boundary of the domain is defined as the central axis, and adjacent to the channel's outer wall, a boundary is defined as the interface between the fluid and solid regions.The meshing of the present model is performed using ANSYS Meshing software. The mesh type is structured, and the number of elements is equal to 9,282.Magnetic Field MethodologyWhen metal or alloy particles of very small dimensions, on the order of the nano-scale, are mixed into a base fluid, a nanofluid is produced. Such fluids have applications such as enhancing heat transfer thanks to the conductivity of the metals.In this simulation, the effect of a magnetic field on the nanofluid's behavior and heat transfer is investigated. For this purpose, the magnetohydrodynamic (MHD) model is used, and the magnetic field is defined using the magnetic induction method. With this method, an external magnetic field is generated to apply a specific magnetic flux in different directions of the Cartesian coordinate system.The nanofluid defined in the model is based on iron oxide (Fe₃O₄) and contains 2% nanoparticles. It has a density of 1081.158 kg/m³, a specific heat capacity of 3841 J/kg·K, a thermal conductivity of 0.640835 W/m·K, and a viscosity of 0.001055 kg/m·s. A constant magnetic field is applied, with a magnetic flux of 1 tesla defined only along the y-axis, corresponding to the radial direction of the channel.In terms of boundary conditions, an insulation condition is applied to the outer wall of the channel, meaning that no electric current passes through it. For the inner wall and the common boundary between the solid and fluid parts of the model, a coupling condition is used to transmit electric current in both directions. The nanofluid stream enters the channel with a velocity of 0.0837 m·s⁻¹ and a temperature of 300 K, and exits at a pressure equal to atmospheric pressure. The outer wall of the channel is held at a constant thermal condition with a temperature of 320 K.The laminar model and the energy equation are enabled to solve the fluid flow equations and to calculate the temperature distribution inside the domain, respectively.Magnetic Field ConclusionAt the end of the solution process, two-dimensional contours of pressure, velocity, temperature, and the magnetic field in the horizontal and vertical directions are obtained. In addition, a diagram of the perpendicular magnetic field variation along the longitudinal direction of the channel's central axis is produced. The present results show the effect of applying a magnetic field and a thermal boundary condition on the nanofluid flow and its heat transfer.