DescriptionThis project simulates the HVAC system of an operating room using ANSYS Fluent, focusing on how the ventilation design manages contamination around the patient and surgical team. The system relies on laminar airflow to keep the room's air clean, with air entering from ceiling panels and moving downward through the space, sweeping contaminants, assumed to originate from the patient's body, toward the room's corners and eventually out through lower exhaust panels. A linear air curtain plays a key role in this process, forming a barrier that stops contaminated air from circulating back toward the patient once it has been displaced. The geometry, representing the hospital room and its HVAC layout, is built in Design Modeler and meshed in ANSYS Meshing with an unstructured grid of 4,137,570 cells.MethodologySince the central goal is tracking how pollutants, oxygen, nitrogen, and humidity distribute through the room simultaneously, the Species Transport model is used, solving a separate transport equation for each of these gas-phase components rather than treating the air as a single uniform species.AnalysisThe solution yields contours of velocity, pressure, temperature, and species mass fraction for both oxygen and contaminants, along with 2D velocity vector fields. The temperature contours confirm that incoming conditioned air successfully cools the region around the patient's body, which is a strong heat source, indicating the cooling function of the system is working as intended. The velocity vectors show fresh air descending from the ceiling panels and spreading sideways as it reaches the room, a pattern that initially carries contaminants toward the patient's surface before the air curtain intervenes, generating a strong flow barrier that redirects the contaminated air toward the room's sides and ultimately to the outlet panels rather than letting it return to the patient. The contaminant mass fraction contours track this same pattern closely, confirming that the HVAC system, once the air curtain effect is accounted for, effectively clears contaminants from the patient's vicinity and channels them out of the operating room.

DescriptionThis project studies solar-driven heat transfer and natural convection inside a room-and-balcony configuration using ANSYS Fluent. The balcony has a glass roof and one glass wall, and as sunlight radiates into both spaces, buoyancy-driven natural convection becomes the dominant mechanism circulating air within them, since no fans or external forcing are present to drive the flow. The geometry, comprising the room and balcony together, is built in 3D in Design Modeler and meshed in ANSYS Meshing with a structured grid of 290,250 elements.MethodologyNatural convection here arises purely from buoyancy: as sunlight warms parts of the air, that air loses density and rises, drawing in cooler, denser air to replace it, and this exchange repeats to form a self-sustaining rotating flow. Turbulence is resolved with the standard k-epsilon model, while the P1 solar ray tracing model simulates incoming sunlight and calculates the radiative heat transfer it produces inside the room. The energy equation is active to compute the resulting temperature field, and density is allowed to follow the ideal gas law so that thermally driven buoyancy is captured directly rather than assumed. Ambient air is set at 310 K with a heat transfer coefficient of 20 W/m²K, the room's walls are treated as opaque absorbers of solar radiation, and the glass walls and roof are modeled as semi-transparent, letting solar rays partially pass through into the interior.AnalysisThe results include 2D and 3D contours of velocity, temperature, and pressure, along with streamlines through both spaces. The pressure fields show clear stratification characteristic of natural convection in an enclosed volume, and notably, the pressure distribution in the room runs opposite in direction to that in the balcony, a difference traced to the glass roof: air near that glass boundary tends to stay warmer, which impedes the usual replacement of cool air by hot air and causes air to accumulate lower in the balcony than the convection pattern would otherwise predict. Temperature contours confirm the room reaches noticeably higher temperatures than the balcony, consistent with the room's opaque walls absorbing far more solar heat than the balcony's semi-transparent glass. The streamlines make the underlying convective rotation visible in both spaces, tracing directly how buoyancy-driven circulation moves air through the room and balcony.

DescriptionThis project simulates an air conditioning system that uses phase change material (PCM) as its thermal storage medium, modeled in ANSYS Fluent. PCMs are organic compounds that absorb and store large amounts of latent heat as they melt, drawing heat from the surrounding air and cooling the room during hot periods, then release that stored heat back as they re-solidify, providing warmth during cooler periods. The specific PCM used here is rubidium-rt20, with a density of 1480 kg/m³, specific heat of 2500 J/kg·K, thermal conductivity of 0.6 W/m·K, and viscosity of 0.164428 kg/m·s. The model is a 2D rectangular domain of 0.09 m × 0.5 m containing four distinct PCM zones, built in Design Modeler and meshed in ANSYS Meshing with a structured grid of 45,000 elements. Given the time-dependent nature of the phase change process, a transient solver is used throughout.MethodologyThe PCM behavior is captured through Fluent's Solidification and Melting model, with the phase transition defined by a solidus temperature of 295.15 K, a liquidus temperature of 297.15 K, and a latent heat of melting of 150,000 J/kg, giving the material a very narrow 2 K melting range characteristic of organic PCMs. Warm air enters the domain horizontally from the upper inlet at 0.018 kg/s and 302.15 K, exits at atmospheric pressure through the lower outlet, and as it passes the PCM zones, the temperature difference drives heat transfer into the material and triggers melting. Turbulence and temperature distribution are resolved with the RNG k-epsilon model and energy equation, and the simulation runs with a time step of 0.5 s.AnalysisThe results include 2D contours of pressure, velocity, temperature, and liquid mass fraction extracted at multiple time steps throughout the simulation. The temperature and liquid mass fraction contours together show the PCM progressively melting over time as it absorbs heat from the warm airflow, with the liquid fraction increasing steadily as the simulation advances. Pressure and velocity fields, by contrast, stabilize relatively quickly and remain approximately constant thereafter, indicating that the flow field reaches a quasi-steady condition while the slower phase change process continues to evolve in the PCM zones.

Series Fans CFD Simulation Using MRF Method in ANSYS FluentIntroductionThis project investigates the steady-state airflow behavior between two 3-bladed series fans rotating at an angular velocity of 300 rpm using ANSYS Fluent, employing the Multiple Reference Frame (MRF) method to capture the rotational effects of the fan blades on the surrounding flow field.Geometry and MeshThe three-dimensional geometry of the dual fan assembly was designed in SpaceClaim, and the domain was meshed using ANSYS Meshing, resulting in a total element count of 1,914,000.MethodologyThe rotation of the fans generates air suction at the inlet boundary, with a volumetric flow rate of 2.95755 m³/s. Along the domain centerline, air velocity reaches values up to 25 m/s, while the maximum velocity in the entire domain, 47.05 m/s, occurs downstream of the first fan. Turbulent flow behavior throughout the domain was resolved using the RNG k-epsilon turbulence model.Results and ConclusionTwo- and three-dimensional contours of pressure, velocity, velocity vectors, and streamlines were generated to characterize the flow field. Based on the calculated Fluent data, the air mass flow rate at the inlet equals 3.62019 kg/s. A comparison of the pressure drop across each fan reveals that the first fan produces a pressure drop roughly twice that of the second fan, at 500 Pa and 230 Pa, respectively. Negative gauge pressure is observed downstream of both fans, with the region downstream of the first fan reaching a value five times lower than that of the second fan, at -500 Pa compared to -100 Pa. Consistent with the higher pressure drop, the velocity magnitude downstream of the first fan is also higher, at 28 m/s, compared to 12 m/s downstream of the second fan, confirming that the first fan experiences a more significant aerodynamic loading within the series configuration.

DescriptionThis simulation models a dehumidifier using ANSYS Fluent. A dehumidifier is an air-conditioning device that reduces and maintains the humidity level of the air. It is used to improve people's health and thermal comfort, eliminate musty odors, and prevent mildew growth by removing water from humid air.This project investigates a humidification–dehumidification system based on a phase-change process. These systems consist of two sections: the evaporator and the condenser. First, the airflow inside the copper pipes is heated and compressed by the compressor and then directed to the condenser section. In this section, the temperature of the air inside the pipes is reduced by the blowing fan, and condensation occurs. The resulting liquid then moves to the evaporator section, where it absorbs heat, evaporates, and returns to the gas phase. This heat is drawn from the humid air blown over the pipes, and because the humid air gives up its heat, dry air is obtained.In this study, the humid air is treated as water vapor. Therefore, a multiphase model consisting of water and vapor must be defined. The mass transfer between vapor and water is then defined as an evaporation–condensation type, so that steam turns into liquid water when the temperature drops below the saturation temperature. The amount of water produced by the phase change between vapor and water indicates the degree of dehumidification. Since the two phases of water and vapor are entirely separate from each other, the Volume of Fluid (VOF) model is used. Accordingly, a chamber is designed with spiral tubes, so that the pipes carry a flow of cold water while the chamber contains water vapor. The vapor enters the chamber at a saturation temperature of 373.15 K and a velocity of 0.05 m/s and contacts the surface of a pipe carrying water at a temperature of 358.15 K and a velocity of 0.01 m/s.Geometry & MeshThe present geometry is designed as a 3D model using Design Modeler. The computational zone is the interior of a dehumidifier, which consists of a chamber with spiral tubes. Steam flows inside the chamber, and cold water flows inside the spiral pipes. The mesh of the present model is generated using ANSYS Meshing. The mesh is unstructured, and the number of cells produced is equal to 1,522,772.Set-up & SolutionSeveral assumptions are applied in this simulation. A pressure-based solver is used, and the simulation is steady. The effect of gravity is considered, with the gravitational acceleration defined as 9.81 m/s².For the models, the realizable k-epsilon model is selected to account for turbulence, together with the standard wall function for near-wall treatment. The multiphase flow is captured using the VOF model with two Eulerian phases (water and vapor), sharp interface modeling, and an evaporation–condensation mass transfer mechanism. The energy equation is also enabled.The boundary conditions are defined as follows. The wet-air inlet is set as a velocity inlet with a velocity magnitude of 0.05 m·s⁻¹, a temperature of 373.15 K, a water volume fraction of 0, and a vapor volume fraction of 1. The cool-water inlet is likewise a velocity inlet, with a velocity magnitude of 0.01 m·s⁻¹, a temperature of 358.15 K, a water volume fraction of 1, and a vapor volume fraction of 0. The dry-air outlet is defined as a pressure outlet with a gauge pressure of 0 Pascal, and the cool-water outlet is also a pressure outlet with a gauge pressure of 0 Pascal. The inner wall is a stationary wall with a coupled thermal condition, while the outer wall is a stationary wall with a heat flux of 0 W·m⁻².Regarding the solution methods, the pressure–velocity coupling is handled with the Coupled scheme. The PRESTO! scheme is used for pressure, and the modified HRIC scheme is used for the volume fraction. First-order upwind discretization is applied to the momentum, turbulent kinetic energy, turbulent dissipation rate, and energy equations.Finally, the solution is initialized using the standard method. The gauge pressure is set to 0 Pascal and the velocity to 0 m·s⁻¹ throughout the domain. The chamber is patched with a vapor volume fraction of 1 and a temperature of 373.15 K, while the tube is patched with a vapor volume fraction of 0 and a temperature of 358.15 K.

DescriptionThis project simulates the radiation of solar rays into the interior of a room using ANSYS Fluent, taking into account a wooden partition acting as solar shading together with a double-glazed façade. Argon gas fills the gap between the two panes of the double glazing; because argon has a low thermal conductivity, it acts as an insulating layer that reduces heat transfer from the outdoor environment into the room. Radiative heat transfer from the sun is the central physics of the study, so a radiation model is used — here the P1 model — together with the solar ray tracing feature to define the incoming solar radiation.The room is located at a latitude of 24 degrees and a longitude of 26 degrees, with the case set at 1 p.m. on the 30th of June. The directions of the sun's rays are computed from the room's geographic longitude and orientation. The glass walls adjacent to the room are defined as semi-transparent, meaning the sun's rays can be absorbed, transmitted, or reflected at these surfaces. The solar shading, by contrast, is treated as an opaque body that only absorbs and reflects the rays and does not allow them to pass through.Geometry & MeshThe model was built in 3D using Design Modeler and represents a room connected to an outdoor space through a wooden partition (solar shading) and a double-glazed façade. The room is 6 m deep, 5 m wide, and 3 m high, and the gap between the panes of the double glazing is 2 mm. Meshing was performed in ANSYS Meshing using a structured grid of 239,760 elements.MethodologySeveral assumptions underpin the simulation: a pressure-based solver is used, the simulation is steady, and gravitational effects on the fluid are neglected.Viscous model — standard k-epsilon with standard wall functionsRadiation model — P1, with the solar ray tracing solar-load modelEnergy — enabledBoundary conditions — Glass 1: stationary wall, convection thermal condition (heat transfer coefficient 20 W/m²·K, free-stream temperature 310 K), semi-transparent; Glass 2 and Glass 3: stationary walls, coupled thermal condition, semi-transparent; Wood (solar shading): stationary wall, coupled thermal condition, opaque; Room and Argon walls: stationary walls, convection thermal condition (20 W/m²·K, 310 K), opaqueMethods — SIMPLE pressure-velocity coupling; second-order for pressure; second-order upwind for density, momentum, and energy; first-order upwind for turbulent kinetic energy and dissipation rateInitialization — standard method, with 0 Pa gauge pressure, zero velocity, and a temperature of 310 KConclusionOn completion of the solution, two- and three-dimensional results for temperature, pressure, and velocity were obtained, along with velocity information on a plane through the middle of the model. The results clearly show the circulation of air within the room's interior spaces and the rise in temperature throughout the domain caused by the solar radiation.Overall, the study demonstrates how the P1 radiation model combined with solar ray tracing captures the entry of solar energy through a double-glazed, semi-transparent façade and the moderating effect of the wooden solar shading — illustrating how radiative solar loading drives the thermal behavior of a room and how shading and insulated glazing can be used to control it.

DescriptionThis project investigates how solar radiation intensity and angle vary with time of day and their effect on surface temperatures and airflow in an outdoor urban environment, simulated in ANSYS Fluent. The study is anchored to a specific real-world location — Baku, Azerbaijan — and two specific times on June 21st, 8 AM and 3 PM, chosen to contrast morning and afternoon radiation conditions at the same site on the year's longest day. The environment includes a house, trees, and ground, with soil, brick, and wood material properties assigned respectively, so that conduction through solids, convection in the surrounding air, and solar radiation are all represented simultaneously. Free airflow passes through the domain at 10 m/s and 27°C. The geometry is built in Design Modeler and meshed in ANSYS Meshing with an unstructured grid of 2,054,294 cells.MethodologyRadiation is modeled using the Discrete Ordinates (DO) model, the most comprehensive of Fluent's radiation formulations, capable of handling scattering, semi-transparent media, specular surfaces, and wavelength-dependent transitions by solving the radiative transfer equations over a finite set of discrete solid angles. Solar radiation is introduced through the Solar Ray Tracing model, with Baku's longitude, latitude, time zone, and the specific date and hour provided to the solar calculator, which derives the corresponding irradiation intensity and sun angle for each of the two time cases.AnalysisThe results include temperature and radiation heat flux contours for both the 8 AM and 3 PM cases. The maximum domain temperature rises from approximately 312 K at 8 AM to 318 K at 3 PM, a 6 K increase attributable to the higher radiation intensity and more direct sun angle later in the day. In shaded zones between the houses and under the tree canopy, however, the radiation flux received remains in the relatively narrow range of 50 to 70 W/m² across both time cases, indicating that shaded areas provide meaningful and consistent protection from the stronger afternoon solar load even as the broader environment heats up significantly.

Radiation Heat Transfer in a Computer Room — ANSYS Fluent CFD SimulationDescriptionThis project simulates the air conditioning of a computer room containing four computers using ANSYS Fluent. The model represents a computer room with several distinct heat sources and was built in 3D using SpaceClaim. Because the geometry is symmetric, only one-quarter of the room is modeled to reduce computational cost.Meshing was performed in ANSYS Meshing, producing 809,037 elements.MethodologyIn this simulation, steady airflow enters the domain through several inlets at the bottom of the room and exits through several outlets in the ceiling, with radiation heat transfer taken into account. This air-conditioning approach is widely used in office environments; it offers greater energy efficiency because the flow rises naturally through the density difference and buoyancy body force rather than being forced mechanically.Fresh air enters the computational domain at a velocity of 0.61254 m/s and a temperature of 291.8 K. One of the room's four main walls is subjected to a constant heat flux of 194 W/m². The remaining heat sources include a laptop and a simulator, with heat fluxes of 153.25 W/m² and 90.56 W/m², respectively.The Realizable k-epsilon model is used to solve the turbulent flow equations. The energy equation is enabled to compute the temperature variation within the domain, and the ideal gas model is used to capture the change in air density with temperature. Most importantly, the Surface-to-Surface (S2S) radiation model is employed to simulate the radiative heat exchange between surfaces inside the domain.ConclusionThe mixture mass flow rate at the computer room outlet is 0.568 kg/s. Air density reaches its minimum on the surfaces subjected to heat flux: as the fluid temperature rises, its density falls, and the resulting upward buoyant force acts on the fluid volume. As a consequence, the air density decreases progressively with height up the room.High temperatures of around 327 K are observed on the laptop surfaces and the hot walls. Intense turbulence appears near the hot wall and above the simulator, a direct result of the high heat fluxes assigned to the laptop, the simulator, and the hot wall.

Data Center Cooling — ANSYS Fluent CFD SimulationDescriptionThis project simulates and evaluates the cooling performance of a data center using ANSYS Fluent. Data centers face increasingly demanding thermal-management challenges as rack power densities rise, particularly under AI and compute-intensive workloads, making effective cooling one of the central concerns in data center design and operation. The simulation targets the key factors that govern rack cooling performance: cold-air supply outlet placement, supply pressure, and the airflow-management strategies that prevent hot and cold air from mixing inefficiently. As the capstone of the Porous Media: Beginner CFD Training Package, this project applies the porous-zone model at full system scale, using porous media to represent server racks in a large, practical cooling problem.MethodologyThe server racks are modeled as porous media, representing their resistance to airflow in a computationally practical way while capturing the essential pressure-drop and flow-distribution behavior that determines how well cold air penetrates and cools the equipment inside each rack. Rather than resolving the detailed internal geometry of every rack, the porous-zone approach imposes an equivalent resistance, making a full data-center simulation tractable while still reproducing how the cold air distributes across the room and through the racks. The study examines the influence of the cold-air supply outlet placement and the supply pressure on the resulting cooling performance.AnalysisThe results demonstrate the critical role that outlet placement plays in overall cooling effectiveness. Positioning the cold-air supply outlet too close to the cooling unit causes cold-air bypass, where the supplied air short-circuits back toward the cooling unit without reaching the rack inlets, wasting airflow capacity and degrading cooling efficiency. Excessive supply pressure produces a similar outcome: the cold air streams past the front faces of the racks rather than entering them, again resulting in wasted airflow and insufficient rack cooling. Together, these findings give a clear, practical basis for data center layout decisions — specifically, that both outlet proximity and supply pressure must be carefully controlled to ensure cold air is actually delivered where the heat loads are, rather than bypassed before it can do useful work. By the end of this project, you'll be able to model server racks as porous zones in a data-center cooling simulation, study how outlet placement and supply pressure drive cold-air bypass, and interpret the flow and cooling results that inform effective data-center layout.

DescriptionThis project simulates the airborne transmission of coronavirus particles among airplane passengers via breathing, using ANSYS Fluent, in response to the well-documented risk that close passenger spacing on aircraft poses for disease spread. The computational domain represents an airplane cabin with rows of seats, one passenger modeled per seat, and each passenger's mouth defined as a surface source for exhaled breath and virus-laden droplets. Since maintaining physical distance is difficult in a cabin, the goal is to characterize how far and how effectively breath-borne virus particles travel between nearby passengers under the aircraft's actual ventilation conditions. The geometry is built in 3D in SpaceClaim and meshed in ANSYS Meshing with an unstructured grid of 1,316,384 elements.MethodologyVirus-laden droplets are modeled with a density of 1000 kg/m³, specific heat of 1680 J/kg·K, viscosity of 0.000172 kg/m·s, and surface tension of 0.03 N/m, released from each passenger's mouth during breathing. Since the goal is tracking a discrete population of droplets moving through the continuous cabin airflow, the Discrete Phase Model (DPM) is used, with the particles defined as inert and injected as a surface injection through each passenger's mouth inlet, at a diameter of 0.000001 m, temperature of 308 K, velocity of 0.05 m/s, and flow rate of 0.0000221 kg/s. The cabin's ventilation is represented in detail: fresh air enters from ceiling vents at 2.36 m/s and 292.65 K, from side vents at 0.3 m/s and 292.65 K, and from under-seat vents at 0.59 m/s and 292.65 K, while spent air exits through two lower-side outlets held at atmospheric pressure.AnalysisThe solution yields particle tracking based on residence time, along with 3D temperature and velocity contours throughout the cabin. These results show the virus-laden particles leaving the mouth and being picked up by the surrounding ventilation flow, tracing how the cabin's air circulation pattern carries exhaled droplets toward or away from neighboring passengers. This confirms the model captures its intended purpose: showing how the interaction between passenger breathing and the aircraft's specific airflow pattern governs the pathway and residence time of virus-carrying particles in an enclosed cabin environment.