Pool Boiling of Water around Horizontal Tube, CFD Simulation, ANSYS FluentDescriptionPool boiling is one of the most important processes occurring across a wide range of small- and large-scale industries, from petrochemical plants to gas refineries and pharmaceutical manufacturing. This project simulates pool boiling around a cylindrical heater positioned within a rectangular pool filled with water — the heater causes water molecules near its surface to boil and transition into the vapor phase.The geometry was built in SpaceClaim, with ANSYS Meshing used to generate a fine mesh grid totaling 92,151 cells.MethodologyWhile several existing studies examine pool boiling under steady or pseudo-steady conditions, this project focuses specifically on transient pool boiling, aiming to capture and track individual vapor bubbles as they form and rise. The Eulerian multiphase model was used to represent the liquid water phase and the vapor bubble phase, incorporating drag, lift, wall lubrication, turbulent dispersion, turbulent interaction, virtual mass, and surface tension forces — all defined using correlations established in the literature.Turbulent behavior around the bubble formation region near the cylindrical heater was captured using the Realizable k-epsilon model. The domain walls were treated as thermally insulated, while the cylindrical heater surface itself was maintained at 107°C to drive boiling in water initially at 100°C. An adaptive time step was used, with a minimum step of 10⁻⁵ s and an initial step of 10⁻⁴ s.ConclusionThe results confirm that this simulation accurately captures bubble formation and rise, closely matching behavior observed in experimental studies. As expected, velocity and vapor volume fraction contours show bubbles forming within a thin layer surrounding the cylinder before rising toward the pool surface.Heat flux and heat transfer coefficient contours further reveal a substantial flux generated at the heater wall, with a significant amount of heat escaping from the heater into the surrounding water. The simulation ultimately predicted a heat transfer coefficient of 1322 W/m²·K and a heater wall heat flux of 9055 W/m², quantifying the pool boiling heat transfer performance captured in this study.

Wet Steam for Condensation inside a Steam Ejector, ANSYS FluentDescriptionThis project simulates the steam condensation process occurring within an ejector using ANSYS Fluent. An ejector is a mechanical device that uses an actuator (driving) fluid to draw in a secondary material — the two actuator fluids and the suction substance ultimately mix and exit together as a single stream. Ejectors serve two primary functions: vacuuming/suctioning gases and mixing fluids.Structurally, an ejector takes the form of a convergent-divergent tube. As the driving fluid enters and passes through the nozzle's converging section, the reducing cross-sectional area increases flow velocity according to the continuity equation — effectively converting the fluid's potential energy into kinetic energy. Per Bernoulli's principle, this increasing velocity corresponds to a drop in fluid pressure, which in turn drives the suction effect central to the ejector's operation.The 2D geometry was designed in Design Modeler, representing an axisymmetric plane of the ejector: 0.411 m in length, with a 0.02 m wide exit, a 0.0038 m wide first entrance, and a 0.0165 m wide second entrance. The model's lower edge was defined as an axis of rotation, allowing the 2D geometry to represent the full 3D structure — a simplification made possible by the ejector's perfectly symmetrical geometry, reducing computational cost significantly.The domain was meshed in ANSYS Meshing using a structured grid totaling 25,984 cells.MethodologyThe Wet Steam multiphase model solves two coupled sets of transport equations: the mass fraction of the condensed liquid phase, and the number/concentration of droplets per unit volume. This phase-change model captures the formation of liquid droplets during a homogeneous, non-equilibrium condensation process, based on classical non-isothermal nucleation theory.As superheated dry steam rapidly expands through the ejector, it cools and forms a nucleating core — ultimately producing a two-phase mixture of saturated steam and liquid droplets known as wet steam. A density-based solver was used throughout to capture this compressible, phase-changing flow.ConclusionThe resulting pressure drop generates a compressive vacuum within the ejector, drawing the secondary material into the flow. The primary driving fluid and the entrained secondary material mix and compress together within the diffuser section downstream.Results include 2D contours of pressure, velocity, temperature, turbulent kinetic energy, and the rate of liquid mass generation (equivalent to the condensation rate) — with 3D contours obtainable by rotating these 2D results around the central axis. The liquid mass generation rate stands out as one of the most important results, offering direct insight into how effectively and where condensation occurs throughout the ejector's convergent-divergent geometry.

Cavitation in a Radial Flow Pump CFD Simulation, ANSYS Fluent TutorialDescriptionThis project simulates the cavitation phenomenon inside a radial flow pump using ANSYS Fluent. This centrifugal (radial flow) pump draws fluid in parallel to its central axis and discharges it radially, perpendicular to the inlet path — a configuration commonly used to generate high pressures at relatively low flow rates, and among the most widely used pump types overall.Cavitation occurs when a liquid's local pressure drops below its vapor pressure at a given temperature, causing the fluid to transition from liquid to vapor and form bubbles. If these bubbles subsequently travel into higher-pressure regions of the pump, they collapse — this collapse generates a localized vacuum, drawing the surrounding liquid inward at very high speed and pressure, often striking nearby walls and blades with enough force to cause damage and shorten pump lifespan.MethodologyThe working fluid was liquid diesel, defined with a density of 830 kg/m³ and a viscosity of 0.00332 kg/m·s. Since pumps operate fundamentally on pressure differences, pressure boundary conditions were applied at both the inlet and outlet — diesel entered axially at 0 Pa and exited radially at 109,872 Pa. Fluid rotation within the pump was captured using the Moving Reference Frame (MRF) approach, with a rotational speed of 20 rad/s.To specifically investigate cavitation risk, a second fluid — diesel vapor — was defined with a density of 9.4 kg/m³ and a viscosity of 0.000007 kg/m·s, using the VOF multiphase model. Liquid diesel served as the primary phase and diesel vapor as the secondary phase, with mass transfer between them governed by the cavitation model, using a vapor pressure threshold of 50,900 Pa to trigger phase change.The 3D geometry was designed in BladeGen. Given the model's radial symmetry, only a single blade passage was modeled — featuring an axial inlet section on one side and a radial outlet section on the other, with periodic boundary conditions applied on both sides and a single blade drawn as a curved profile through the middle. Expanding this single-piece geometry around the central axis produces the full radial flow pump, featuring seven blades in total. The domain was meshed in TurboGrid using a structured grid totaling 63,308 elements.ConclusionResults include 3D contours of pressure, velocity, vapor phase volume fraction, liquid phase volume fraction gradient, and mass transfer rate gradient, along with 3D velocity vectors. The most critical results — vapor volume fraction and mass transfer rate contours — directly identify the specific locations within the pump where cavitation occurs, offering insight essential for evaluating cavitation risk and informing design changes aimed at mitigating pump damage and extending operational lifespan.

Cavitation Flow Through an Axial Inducer CFD Simulation, ANSYS Fluent TutorialDescriptionThis project simulates cavitation flow through an axial inducer using ANSYS Fluent. Cavitation is the phenomenon by which vapor bubbles form in regions of a fluid where local pressure drops sufficiently low. While it's often assumed that liquid pressure reaching vapor pressure (Pv) is the sole cause, several other factors — velocity being a particularly significant one — also contribute to cavitation onset. The resulting bubble collapse can cause substantial problems, including corrosion, which is especially evident in water pumps, and is typically identified through the characteristic sound and mechanical vibration it produces.Several strategies help reduce cavitation, including increasing pump inlet pressure by reducing the distance between the pump and its supply tank, or reducing pressure drop and flow turbulence more broadly. As industry increasingly demands smaller, higher-speed pumps, improving impeller suction performance has become correspondingly more important. Inducers are components installed ahead of the main impeller, rotating at the same speed, specifically to boost inlet pressure and improve suction performance — making cavitation reduction one of the primary reasons inducers are used in pump systems.The geometry was designed in Design Modeler and meshed in ANSYS Meshing using an unstructured grid totaling 938,174 cells.MethodologyThe inducer's rotational motion was defined using the Frame Motion method, with the fluid surrounding the inducer blades assigned a rotational speed of 15,000 rpm. Since cavitation fundamentally involves a phase change between liquid and vapor, a multiphase model was required — specifically the VOF model, chosen for its ability to sharply resolve the separation boundary between the two phases, with liquid defined as the primary phase and vapor as the secondary phase.ConclusionResults include contours of velocity, pressure, and liquid/vapor mass fraction, along with streamlines around the inducer. The results show that fluid pressure increases as it passes through the inducer — if connected to a pump, this represents the inducer's output pressure and the maximum pressure delivered to the downstream impellers. Suction pressure at the back of the inducer also increases, directly improving the pump's overall suction performance.Velocity contours and streamlines show peak velocity occurring near the inducer, driven by its angular rotation, while volume fraction contours confirm a reduction in cavitation — with the proportion of liquid water present substantially exceeding that of vapor, indicating that the inducer successfully suppresses cavitation formation as intended.

Multicomponent Particle Type for Droplets, CFD Simulation ANSYS Fluent TrainingDescriptionThis project investigates the multicomponent particle type for droplet modeling using ANSYS Fluent, employing a one-way DPM approach to simulate the discrete phase.The 3D geometry was built in SpaceClaim, with a computational domain 100 mm long and 20 mm in both height and width. The domain was meshed in ANSYS Meshing using an unstructured grid totaling 56,245 cells.MethodologySeveral assumptions were applied to the simulation: a pressure-based solver was used, the simulation was run as unsteady, and gravitational effects were excluded.Key simulation settings included:Viscous model: k-omega SSTDiscrete phase: Enabled with unsteady particle tracking; injected material defined as a hydrogen peroxide-water mixture, using the multicomponent particle type with a cone injection configurationBoundary conditions: Velocity inlet (drying air) at 0.2 m/s and 450 K, with discrete phase set to escape; pressure outlet at 0 Pa gauge pressure with discrete phase set to escape; stationary walls with discrete phase set to reflectSolution methods: SIMPLE pressure-velocity coupling, second-order discretization for pressure, second-order upwind for momentum, and first-order upwind for the modified turbulent viscosityInitialization: Hybrid methodThe injected droplets consist of two mixed species — water and hydrogen peroxide — modeled using the multicomponent particle type, which allows each species within a single droplet to behave independently: water is defined as evaporating, while the second species is treated as non-evaporating.ConclusionThe results clearly show water evaporating from within the droplets, accompanied by a corresponding decrease in droplet diameter over time — confirming that the multicomponent particle model successfully captures the differential evaporation behavior between the two species present in each droplet, with only the water fraction evaporating while the hydrogen peroxide fraction remains, consistent with how the two components were defined.

Diesel Injection at High Pressure, Penetration Length AnalysisDescriptionThis project simulates diesel injection at high pressure (500 bar) under an elevated environmental pressure (10 bar), analyzing the diesel spray's penetration length and jet angle — both critical parameters for optimizing combustion efficiency and reducing emissions in diesel engines. A two-way Discrete Phase Model (DPM) captures the interaction between diesel droplets and the surrounding air, with results visualized through animations and plots of velocity, pressure, and droplet diameter at multiple time steps.The geometry of the diesel injector and combustion chamber was built in SpaceClaim, accurately representing the nozzle and spray region. The domain was meshed in ANSYS Meshing, with refinement concentrated near the injector nozzle to resolve the high velocity and pressure gradients occurring there. The final mesh totals 1,250,256 cells, balancing computational accuracy with efficiency.MethodologyThe simulation was configured to handle multiphase flow dynamics, capturing the interaction between the discrete diesel droplet phase and the continuous air phase through a two-way coupled DPM, accounting for momentum and energy exchange between the two phases. Turbulence was resolved using the Realizable k-epsilon model, chosen for its robustness and accuracy in high-Reynolds-number turbulent flows relevant to droplet mixing and dispersion.Boundary conditions included an injection pressure of 500 bar — ensuring fine fuel atomization and improved air mixing — and an environmental (chamber) pressure of 10 bar, representative of real diesel combustion chamber conditions. Diesel fuel was modeled with a density of 830 kg/m³ and a viscosity of 2.7 mPa·s. Injection was simulated using pressure swirl atomizers, a configuration widely used in diesel engines to achieve fine, uniform spray distribution.ConclusionThe penetration length results show an initial rapid increase, consistent with the high 500 bar injection pressure, followed by a slower increase and eventual stabilization as the spray droplets undergo atomization and dispersion — behavior shaped by turbulence, droplet size, and environmental pressure. These trends offer a useful basis for evaluating and refining pressure swirl atomizer design to achieve desired spray characteristics under specific operating conditions.Velocity contours show peak velocity concentrated near the nozzle exit, decreasing as the spray propagates into the chamber, while pressure contours reveal a high-pressure region near the nozzle that dissipates as the spray expands outward. Droplet diameter remained small under the 500 bar injection condition, indicating effective atomization — a key factor for efficient combustion and reduced emissions. Accompanying animations capture the spray's transient development, including vortex formation and the ongoing interaction between droplets and the surrounding air.

Water Spraying Considering Breakup and Evaporation, ANSYS Fluent TrainingDescriptionThis project simulates water spraying from a nozzle, capturing the full spectrum of spray behavior — droplet formation, breakup, evaporation, and wall film formation — by combining the Discrete Phase Model (DPM) with the Species Transport model in ANSYS Fluent.The simulation models 2 mm diameter water droplets injected at 1.25 m/s, with evaporation triggered once droplets reach a temperature threshold of 282.5 K. Droplet breakup was captured using the Taylor Analogy Breakup (TAB) model, alongside stochastic collision and coalescence to represent droplet-to-droplet interaction throughout the spray.MethodologyA dynamic-drag law was applied to account for non-spherical droplet shapes as they deform and break apart, while the Discrete Random Walk model captured turbulent dispersion effects on individual droplet trajectories. Surface interactions were modeled using Wall-Film DPM boundary conditions, allowing droplets reaching a surface to realistically stick, rebound, spread, or splash depending on local impact conditions.ConclusionThe results reveal a droplet diameter distribution spanning from 0.002 mm to 7 mm, reflecting the combined effects of breakup and evaporation on droplet population over the course of the spray. Droplet behavior upon surface impact — sticking, rebounding, spreading, or splashing — was captured and analyzed in detail through the wall-film boundary conditions, with the full spray dynamics visualized through animations and contour plots.Together, these results provide a comprehensive picture of how droplet breakup, evaporation, and surface interaction shape overall spray behavior — offering insight directly applicable to nozzle design optimization, spray cooling systems, fuel injection processes, and coating applications where accurate droplet-scale prediction is essential.

Air Freshener Spray in Restroom CFD Simulation, ANSYS Fluent TrainingDescriptionThis project simulates air freshener spray within a restroom using ANSYS Fluent. The 3D geometry was designed in Design Modeler, representing the interior of a restroom, and meshed in ANSYS Meshing using an unstructured grid with the curvature method applied to focus refinement on grid-sensitive areas, totaling 1,187,006 cells.MethodologyThis project investigates air freshener spray behavior using the two-way DPM method. Fragrance particles are physically expelled from the device as water droplets that evaporate into the surrounding space, defined at a temperature of 310 K, a velocity of 50 m/s, and a mass flow rate of 0.018 kg/s, emitted over an interval of 0 to 0.1 seconds. Since droplet diameter isn't constant during diffusion, the Rosin-Rammler logarithmic distribution method was used to represent the resulting range of particle sizes, with minimum, maximum, and average diameters, the distribution's spread parameter, and the number of size classes per injection all determined through this formulation. This droplet-based approach required activating the Species Transport model alongside DPM.Discrete phase boundary conditions were defined as Escape at the device outlet, the restroom inlet, and the toilet outlet — allowing particles to pass freely through these boundaries — while a Trap condition was applied at all walls and heater surfaces, capturing and collecting particles that reach these surfaces. The simulation was run as unsteady, using a time step of 0.01 seconds, with the RNG k-epsilon model and energy equation enabled to resolve turbulent flow behavior and temperature distribution throughout the domain.ConclusionThe results show that the restroom's heater establishes a suitable ambient temperature while also driving rotational airflow throughout the space, which in turn promotes particle evaporation. The accompanying animation further reveals that larger-diameter particles tend to settle at lower positions than smaller particles, owing to their greater mass, before eventually evaporating — offering a clear picture of how fragrance particles disperse, settle, and evaporate throughout the restroom under the combined influence of airflow and heating.

Misting System for Outdoor Ventilation of a Coffee Shop, CFD Simulation TrainingDescriptionThis project simulates a misting system for outdoor ventilation at a coffee shop, modeling a café with two tables positioned under a canopy, with ambient wind blowing at 1 m/s and 305 K. Since the fogging system operates intermittently rather than continuously, a control-based injection approach was used within this transient simulation, specifically investigating the effect of a 0.5-second injection process using the Air/Blast Atomizer model.The 3D geometry was built in Design Modeler, and the domain was meshed in ANSYS Meshing — first generating an unstructured grid, then converting it to polyhedral cells, totaling 2,358,491 elements.MethodologyThe energy equation was enabled to capture temperature throughout the domain, with turbulence modeled using the Realizable k-epsilon model. The misting system itself was simulated using a combination of the Species Transport model and the Discrete Phase Model (DPM), capturing both the evaporating water vapor and the tracked mist droplets.ConclusionInjection begins at 0 s and continues for 0.5 seconds, during which droplet evaporation drives a corresponding decrease in average ambient temperature. The injectors are specifically oriented toward the tables, ensuring customers seated there directly benefit from the misting effect and experience noticeably lower temperatures than the surrounding ambient air.The average temperature on the mid-plane at each table was tracked and plotted, clearly illustrating how effectively the fogging system reduces local temperature at the points where customers are seated — confirming the misting system's practical value for outdoor thermal comfort in this café setting.

Seed Drying Via Hydraulic Mechanism, ANSYS FluentDescriptionThis project simulates seed drying through a hydraulic mechanism process using ANSYS Fluent. Drying refers to the removal of moisture from grain, a process critical for reducing seed moisture content to a safe level that preserves viability and stability during storage — without adequate drying, seeds risk rapid spoilage from mold growth, self-heating, and increased microbial activity.The geometry consists of a simple semi-cylindrical chamber, with a set of spherical shapes positioned inside representing wet seeds. Hot airflow enters from the bottom of the chamber at 303.15 K and 0.15 m/s, moving upward and exiting through the top. As this hot air stream moves through the chamber, it carries moisture away from the seeds — importantly, this occurs through moisture transmission from the seed region to the surroundings, not evaporation, which is what distinguishes this as a hydraulic drying mechanism rather than an evaporative one. For comparison, evaporation-based drying (using the Discrete Phase Model to track individual grain particles) is covered separately in the related "Grain Drying Device" and "Rice Dryer" projects.The 3D geometry was designed in Design Modeler, representing the semi-cylindrical chamber interior with the spherical seed particles positioned at its center. The domain was meshed in ANSYS Meshing using an unstructured grid totaling 6,286,496 elements.MethodologySince the computational domain contains a combination of air and H₂O, the Species Transport model was used to capture this mixture's behavior. The spherical seeds themselves were modeled as porous media, with moisture assumed to have penetrated the internal cavities of each seed, defined with a porosity coefficient of 0.418. The seed zone was initialized as wet, carrying the initial moisture content that the simulation tracks as it dries.ConclusionResults include 2D and 3D contours of temperature, pressure, and velocity throughout the chamber. The results show that moisture (H₂O) content within the seeds progressively decreases as the hot air stream moves upward through the chamber — confirming that the hydraulic drying mechanism successfully transports moisture away from the porous seed particles and out of the domain via the rising airflow.