Carbonate Cake Filtration Simulation Using the Eulerian Multiphase Model — ANSYS Fluent TutorialDescriptionFiltration is one of the most widely used physical separation processes in industry, essential for removing solid particles from liquids in applications such as water treatment and purification, chemical processing, and environmental remediation. As filtration proceeds, the separated solids accumulate on the filter surface and form a layer known as the filter cake. While the cake itself can improve capture efficiency, its continuous growth increases flow resistance and gradually reduces the performance of the filtration unit — making accurate prediction of cake formation a key concern in filter design and operation.This tutorial, part of the Clean Water: Beginner CFD Training Package, presents a complete simulation of carbonate cake filtration in ANSYS Fluent. The model captures the interaction between three phases — water as the carrier fluid, suspended carbonate particles, and the carbon filter medium — allowing you to study how carbonate particles are captured by the filter and how the cake layer develops over time. Whether you are a process engineer, a CFD specialist, or a chemical engineering student, this project provides a practical foundation for simulating industrial separation processes.MethodologyThe filtration unit geometry is created in ANSYS Design Modeler, and a high-quality structured mesh is generated in ANSYS Meshing to ensure accurate resolution of the multiphase flow field.The simulation is built on the Eulerian multiphase model, the most rigorous approach for modeling interpenetrating phases with strong momentum coupling. Key elements of the setup include:Activating the Granular and Packed Bed options to represent the solid carbonate phase and the stationary filter mediumDefining granular phase property models for the granular temperature calculationApplying interphase momentum exchange mechanisms, including drag, lift, and virtual mass forces between each phase pairThe energy equation is enabled to compute the temperature distribution within the domain, and the Ranz-Marshall correlation is used to model heat transfer between the water and the filter phase. Turbulence is modeled with the standard k-epsilon model, providing a robust balance of accuracy and computational cost for this class of flow.AnalysisAt the end of the solution process, contours of phase volume fraction, temperature, and velocity are extracted and interpreted. The results show how the carbonate concentration changes across the filter as particles are progressively captured by the carbon medium, confirming the physical separation of the solid phase from the water stream. The temperature profile of the feed water through the unit is also examined, illustrating the thermal interaction between the flow and the filter.Most importantly, the simulation reveals the dynamics of cake layer formation: carbonate particles accumulate on the filter surface, the cake thickness grows over time, and the added flow resistance begins to affect the filtration performance. These insights demonstrate how CFD can be used to evaluate filter efficiency, optimize filtration unit design, and support decisions on filter maintenance and scale-up for industrial clean-water applications.

Description: Distillation column trays are one of the most important pieces of equipment in clean water treatment, chemical separation, and process engineering, working by bringing rising vapor into direct contact with falling liquid on a perforated tray so volatile components evaporate while heavier components condense and drain. This project focuses on the hydrodynamic two-phase behavior of air and water at the tray location, examining how the two phases interact, mix, and separate, without yet introducing heat transfer or evaporation effects.Methodology: A symmetrical 3D tray column geometry is built in Design Modeler, modeling only half the chamber to reduce computational cost, and meshed with an unstructured grid of roughly 866,000 elements suited to two-phase tray flow. The VOF multiphase model is configured with air as the primary phase and water as the secondary phase, using implicit formulation and sharp interface modeling, alongside mixed boundary conditions of a velocity inlet for gas at 23.35 m/s, a mass flow inlet for liquid at 4 kg/s, and pressure outlets for both phases. Turbulence is captured with the RNG k-ε model and standard wall functions to handle the swirling, separating flow, with PRESTO! pressure discretization and the Modified HRIC scheme for volume fraction, and the domain is initialized with a patched water region to start from a realistic phase distribution.Analysis: Post-processing includes pressure contours, velocity contours, phase volume fractions, and velocity vectors across both 2D cross-sections and 3D views, capturing how the vapor and liquid phases distribute and interact across the tray. Since distillation columns underpin desalination plants, wastewater treatment, and petrochemical refineries alike, this hydrodynamic groundwork provides a portable, industry-relevant foundation for tackling multiphase separation problems in real process equipment.

Home Water Distiller CFD SimulationDescriptionThis project simulates a small-scale home water distiller using ANSYS Fluent, investigating one of the more accessible approaches to water desalination. The system relies entirely on heat transfer and phase change to produce clean water: a floor heater warms water until it evaporates, and because this steam carries none of the original salt, bacteria, or contaminants, cooling it back into liquid form yields pure freshwater. The steam travels through a spiral tube, where a fan cools the surrounding pipe walls, driving the vapor to condense back into fresh water on the other side.The device is built from three functional sections: an evaporator at the bottom where water turns to steam, a condenser at the top where that steam is cooled, and a spiral tube connecting the two that serves as the pathway for vapor transfer and the site where condensation actually occurs. To keep the model manageable, the heater and fan themselves weren't explicitly modeled; instead, fixed temperatures were assigned directly to represent their effects; the evaporator was held at 373 K, matching the saturation temperature of water, while the condenser was set to 363 K. The patch tool was used to define the initial water level inside the evaporator tank.Because the process unfolds over time as water evaporates and vapor condenses, the simulation was run as a time-dependent, unsteady case, allowing the rate of phase change and the resulting freshwater output to be tracked as the system evolves. The three-dimensional geometry was built in Design Modeler, and the model was meshed in ANSYS Meshing using an unstructured grid of 478,805 cells.MethodologyThree phases coexist in this system: liquid water, water vapor, and air, which serves as the coolant inside the condenser. Since these phases need to be tracked with distinct, clearly defined boundaries, the Volume of Fluid (VOF) model was used, with air set as the primary phase and both liquid water and water vapor treated as secondary phases. The Sharp interface option was applied to keep the boundary between phases crisp rather than smeared across a transition layer.The evaporation-condensation process between the water and vapor phases was captured through a mass transfer mechanism based on Lee's equations, which calculate phase-change rates based on the saturation temperature and the evaporation/condensation frequency coefficients. With the saturation temperature set at 373.15 K, any fluid temperature above this threshold triggers evaporation, while any temperature below it triggers condensation.ConclusionThe simulation produced contours of temperature, phase-change rate, and volume fraction for both water and vapor, captured on a mid-plane cross-section at the final second of the 10-second simulation, along with animations tracking how these quantities evolve over time. Plots of freshwater output — both the volume-averaged water fraction inside the system and the mass flow rate of freshwater leaving the condenser — were also generated.The temperature and mass transfer contours line up closely: wherever the fluid temperature drops below the saturation point, condensation occurs, shown by a negative phase-change rate. Inside the evaporator, water evaporates from its surface and rises as steam; once that steam reaches the cooler condenser tube, it condenses back into liquid, producing usable freshwater. The output plots confirm that freshwater production increases steadily over time as more condensation occurs, demonstrating that the desalination system's core evaporation-condensation cycle works as intended.

Flat Plate Solar Collector — Conjugate Heat Transfer (CHT) ANSYS Fluent CFD SimulationDescriptionFlat plate solar collectors (FPSC), and the photovoltaic-thermal (PV/T) systems built around them, convert sunlight into useful heat — most commonly by warming water that flows through pipes bonded to a sun-facing absorber plate. Their performance depends on the collector design, the materials of each layer, and the installation conditions: geographic location and tilt angle directly determine how much solar energy the panel receives.This project uses ANSYS Fluent to simulate an FPSC installed in Doha at a 45° tilt angle, solving the full conjugate heat transfer (CHT) problem to capture how solar radiation heats the water passing through the collector's pipes. Because the model resolves the solid layers, the pipe walls, and the water flow as one coupled thermal system — and includes the heat generated inside the PV layer itself — it represents a true PV/T simulation rather than a simple solar-heating case.MethodologyThe collector geometry is created in Design Modeler, and a tetrahedral mesh of approximately 5,590,000 elements is generated in ANSYS Meshing. A mesh of this size is required to resolve the thin solid layers, the pipe walls, and the water domain together within a single coupled model.The simulation couples three sets of physics:The Navier–Stokes equations for the water flow inside the pipesThe energy equation for heat transfer through both the fluid and the solid layers (conjugate heat transfer)The Discrete Ordinates (DO) radiation model for the incoming solar irradiation, set at 800 W/m²Water enters the collector at 300 K with a mass flow rate of 0.02 kg/s and exits at atmospheric pressure. A key feature of the model is the treatment of the PV layer: instead of representing the panel as a simple absorbing surface, the volumetric heat flux inside the PV layer is calculated from the solar flux, the glass transmittance, the PV absorption coefficient, the panel efficiency, and the PV layer thickness, and is then applied as a volumetric heat source. This physically based heat generation term is what distinguishes the case as a genuine PV/T simulation.AnalysisAt the end of the solution process, temperature contours and volume-averaged results are extracted to evaluate the thermal performance of the collector. The results clearly show how solar radiation progressively raises the water temperature as it travels through the collector pipes: the average water temperature reaches about 306.5 K, while the average PV layer temperature reaches about 310.1 K — the panel running hotter than the water it heats, exactly as expected in a PV/T system.By completing this project, you will be able to set up a coupled CHT simulation with radiation, apply the DO model for solar loading based on location and tilt, implement a volumetric heat source derived from physical panel parameters, and interpret the temperature distribution across a multi-layer solar collector.

DescriptionThis project investigates the performance of a step solar desalination unit (solar still) using ANSYS Fluent, studied through CFD analysis. Producing potable water from saline sources is a central goal of clean water engineering, and the solar still achieves this passively — using nothing but solar energy to convert brackish or seawater into fresh water.The model consists of a small chamber with a sloping glass surface on each side and a series of steps inside, over which saline water flows. Solar radiation passes through the glass to the water surface on the steps, evaporating it; the resulting vapor then meets the cold glass surface and condenses in a distillation process. The freshwater produced by condensation runs down the slope of the glass plate and is discharged as pure water.The model was built in 3D using Design Modeler. Because the geometry is symmetric, only one-quarter of it is modeled. This quarter-geometry comprises two sloping glass surfaces and the steps that carry the water flow. Meshing was performed in ANSYS Meshing, producing 809,037 elements.MethodologyTo convert saline water into fresh water, the water must first be turned into vapor and then condensed back into liquid. A solar still typically consists of a sloped glass cover placed over the device and a stepped platform that holds the saline water to be distilled. The glass cover acts as both a rigid substrate and a transparent layer that admits the sun's rays, while the heat needed to generate vapor comes from the solar energy absorbed inside the device. The vapor then rises, strikes the cool glass cover, and condenses into fresh water.To capture this, the Solar Ray Tracing model is enabled to represent the absorbed solar heat, and the Species Transport model is activated to model the two components — water and vapor — inside the chamber. This approach treats the chamber interior as a water-vapor mixture and does not explicitly simulate the flow of the distilled water. At the start of the simulation, the interior is filled entirely with vapor; the bottom plane of the chamber represents the water surface, and since evaporation occurs there, this surface is treated as vapor.Constant values of 1.00314 × 10⁻⁵ m²/s and 0.0002 kg/m·s are assigned to the mass diffusion coefficient and the thermal diffusion coefficient, respectively, governing the conversion between water and vapor. The sloping plate where the vapor condenses is assumed to consist only of vapor. The ambient air temperature is taken as 311.75 K with a heat transfer coefficient of 25 W/m²K. The stepped platform holding the saline water is assumed to absorb heat with no transmissivity, while the glass cover is assumed to have maximum transmissivity and no absorbance. Gravity is enabled in the Y direction, and the incompressible ideal-gas model is used to account for the density difference between water and vapor.ConclusionOn completion of the solution, three-dimensional contours of velocity, temperature, velocity vectors, and species mass fraction inside the still were obtained.The velocity contours and vectors show how the generated vapor rises within the device to strike the upper sloped glass surface. The 3D temperature contour makes clear that the saline water on the stepped platform has heated up enough to evaporate, while the glass cover remains cold enough to condense the vapor, which then slides down to the lower part of the device where the fresh water is collected. Finally, the species mass fraction contour shows a water mass fraction of one on the stepped platform and the glass substrate, while the water fraction decreases within the interior space — confirming that vapor is forming there. Together, these results demonstrate the complete evaporation-condensation cycle that enables the solar still to deliver clean, desalinated water using only solar energy.

Reverse Osmosis (RO) CFD Simulation, ANSYS Fluent TutorialDescriptionThis project simulates reverse osmosis using ANSYS Fluent.Reverse osmosis is one of the most widely used technologies in clean-water engineering, where it drives desalination and water-purification systems that turn seawater, brackish water, and contaminated supplies into potable water. Understanding how salt and impurities separate across the membrane is central to designing and improving these systems.Osmosis is a natural phenomenon in which a fluid tends to move from a region of lower concentration to one of higher concentration until the concentration on both sides is balanced. Imagine a semi-permeable membrane placed between pure and impure water. By osmosis, water moves toward the impure side until a pressure difference builds up across the membrane. This difference is called the osmotic pressure. If a pressure equal to the osmotic pressure is applied to the impure side, the fluid movement stops. If the applied pressure exceeds the osmotic pressure, the natural direction of flow reverses.Reverse osmosis desalination systems work on exactly this principle: a pressure beyond the osmotic pressure is applied across the semi-permeable membrane, and as the water passes through, salt and impurities are separated from it.This project is simulated in two parts. The first part looks only at fluid behavior driven by osmotic pressure. A closed chamber is modeled and divided into two sections by a barrier that is removed instantaneously. The left side holds a saltwater solution and the right side holds pure water. The goal is to observe how fluid moves between the two sections of different concentration, which illustrates the concepts of osmosis and osmotic pressure.Building on the first part, the second part studies the reverse osmosis desalination system itself. Here a membrane, modeled as a porous medium, is placed in the middle of the chamber. The water-and-salt mixture enters from the inlet on the left and moves toward the membrane. When the solution reaches the membrane, pure water passes through while the salt (the higher-concentration water) is trapped behind it.The geometry was built in two dimensions in Design Modeler as a simple rectangular chamber with a membrane between its two sections. The domain was meshed in ANSYS Meshing using a structured grid of 44,800 cells.Simulation MethodologyBecause an impure solution is used instead of a single pure fluid, a two-phase flow must be defined, so a multiphase model is used. Of the available options (VOF, Mixture, and Eulerian), the Eulerian model, which is the most complex of the three, is used here. Water is the primary phase and salt is the secondary phase dissolved in it, with a salt concentration of 0.02. Concentration is tracked through the volume fraction, and the solver handles the transport equations for that volume fraction.The membrane between the two sections is modeled as a porous medium, where the porosity (the ratio of empty space to total volume) sets its permeability. The simulation runs in two steps: in the first model the fluid moves naturally with no external forces, while the second model applies a driving boundary condition. Since the aim is to study how the system behaves over time, the solution is transient (time-dependent).Results & ConclusionAfter solving, two-dimensional contours of pressure and of the water and salt volume fractions were obtained. Because the solution is transient, the results are compared at different times to capture the system's behavior, and an animation of the change in dissolved-salt volume fraction was produced. Results were obtained for both simulation cases.In the first case (a closed chamber with no external boundary conditions), the left side initially holds water and salt while the right holds pure water. Over time, fluid moves from the higher-concentration side to the lower-concentration side and continues until both sides reach equilibrium. This movement occurs naturally, without external forces, and correctly reproduces the osmotic behavior of the fluid.In the second case, a porous membrane sits in the middle of the system. The water-and-salt solution is driven toward the membrane at a set velocity and pressure beyond the osmotic pressure, opposite to the natural osmotic direction. The results show pure water passing through the membrane while the dissolved salt is trapped behind it. This continues until a fully concentrated solution builds up behind the membrane and pure water collects beyond it. The pressure results also show the pressure difference across the system increasing over time. Together, these results confirm that the reverse osmosis system works correctly and successfully purifies the water.

DescriptionThis project simulates air gap membrane distillation (AGMD) using ANSYS Fluent. Producing potable water from saline or impure sources is a central goal of clean water engineering, and AGMD is one of the membrane distillation technologies developed specifically for this purpose.Water desalination systems fall into two broad categories: thermal desalination and membrane desalination. In the thermal method, a phase change is used to produce fresh water, whereas in the membrane method, specialized membranes separate the water from its impurities. Membrane distillation (MD) systems combine the two approaches — they rely on both a phase change and a dedicated filter membrane. Several MD configurations exist; the one studied here is Air Gap Membrane Distillation (AGMD).The AGMD system consists of four zones: the feed channel, the membrane layer, the air gap, and the cooling channel. Hot water flows through the feed layer while cold water flows in the opposite direction through the cooling layer. The membrane layer sits next to the feed water, and the air gap is placed between the membrane and the cooling channel. In operation, the water first undergoes surface evaporation, and the resulting pure vapor then condenses on the cold surface. For simplicity, the hot feed water is assumed to have already been converted to steam, so saturated steam flows through the feed channel, ready to condense in the air gap.The geometry was modeled in 2D using Design Modeler, and the model was meshed in ANSYS Meshing using a structured grid of 150,000 cells.MethodologyBecause the system involves the steam turning into water through condensation, together with the presence of an air gap, three phases must be represented, so a multiphase model is required rather than a single fluid. The VOF (Volume of Fluid) model is used, since it cleanly separates the different phases and resolves a distinct interface between them — the best choice for capturing a sharp boundary between the water and vapor phases. Air is defined as the primary phase, with liquid water and water vapor as the secondary phases; the volume fraction of each secondary phase is solved through its transport equation.A phase change occurs between the water and vapor phases, so a mass transfer is defined between them based on the evaporation-condensation mechanism. This mechanism governs the phase change between liquid and vapor, with Lee's equations used to calculate the mass transfer rate; these equations depend on the saturation temperature and the frequency coefficients of evaporation and condensation. In addition, the membrane is represented as a porous medium, with a porosity parameter — the ratio of void volume to total volume — defining its permeability.ConclusionOn completion of the solution, contours of temperature, the phase change rate between water and vapor, and the volume fraction of each of the water and vapor phases were obtained.The results show the temperature dropping on the cold side of the air gap, with the temperature contours clearly revealing the thermal boundary layer. The highest condensation (phase change) rate occurs in the regions where the temperature falls, and the negative sign of the phase change rate indicates the transformation from vapor to liquid. Examining the volume fraction contour of the distilled water reveals a film of liquid forming on the cold plate of the air gap; this freshly produced fresh water then runs to the bottom of the air gap under gravity.Overall, the results confirm that the desalination system operates correctly and that the membrane distillation mechanism performs as intended — demonstrating how AGMD converts hot saline feed into clean, condensed fresh water, and how CFD can be used to evaluate and optimize such clean-water technologies.

DescriptionThis project simulates a Humidification Dehumidification (HDH) desalination system using ANSYS Fluent, a core clean water engineering method for producing fresh water from saline sources. The system operates in two coupled stages: a humidifier (evaporator), where hot salt water is sprayed and evaporates into dry air to produce salt-free humid air, and a dehumidifier (condenser), where that humid air contacts cold tube surfaces and condenses into fresh water. This two-step cycle mirrors real-world HDH desalination units, making it directly relevant to sustainable, low-energy freshwater production.MethodologyThe system is modeled in two separate simulations reflecting its two stages. The 3D geometry is built in DesignModeler and meshed in ANSYS Meshing — a hybrid structured/unstructured mesh of 206,928 cells for the humidification chamber, and an unstructured mesh of 553,086 cells for the dehumidification chamber. Cooling tubes in the dehumidifier are simplified using a constant-temperature thermal wall boundary rather than explicit pipe modeling.In the humidification simulation, salt water is introduced as a discrete phase using the Discrete Phase Model, with droplets (1e-6 m diameter) surface-injected over 10 seconds and evaporating into the dry air stream. The Species Transport model tracks the resulting water vapor concentration without chemical reaction, and the internal membrane packing is represented as a porous medium defined by porosity, viscous resistance, and inertial resistance.In the dehumidification simulation, the VOF multiphase model captures the distinct liquid water and water vapor phases, with evaporation-condensation mass transfer defined via Lee's equations based on saturation temperature and phase-change frequency.ConclusionThe humidification stage results, evaluated at the final simulation second, show water vapor mass fraction and discrete particle concentration contours, along with animations tracking droplet spray behavior and vapor mass fraction buildup over time — confirming steady production of humid, salt-free air. The dehumidification stage results show velocity, temperature, mass transfer rate, and phase volume fraction contours, confirming condensation occurring in regions where vapor temperature drops below saturation near the cold tube surfaces, with the highest freshwater yield concentrated around those cooled surfaces. Together, these results validate the HDH system's core function: converting saline water into clean, potable water through a fully coupled evaporation-condensation cycle.

DescriptionThis project simulates a two-stage water desalination device, a system that purifies water through evaporation and condensation rather than filtration, removing even the smallest contaminants that other methods can miss. Water is heated to promote surface evaporation at the bottom of the device, and the resulting vapor rises and contacts cooler sloped surfaces where it condenses back into pure liquid water, directed toward the system outlet. The geometry is built in Design Modeler and meshed in ANSYS Meshing with an unstructured grid of 1,936,581 elements.MethodologyThe VOF multiphase model captures the liquid-vapor interface inside the desalination trays, and since surface evaporation isn't included in Fluent's base solver, a UDF is hooked into the source code to model this mass transfer mechanism directly. The device's bottom surface raises the bulk water temperature to around 353 K, increasing the water molecules' energy and accelerating the evaporation process. Turbulence is resolved with the realizable k-epsilon model, chosen for its accuracy in internal flows, and the energy equation is active given the heat transfer driving the process. The simulation runs transient and in 3D, with gravity enabled so the vapor's upward motion, a consequence of its lower density relative to liquid water, is captured correctly.AnalysisThe results show a stratified pressure distribution inside the system trays, consistent with the hydrostatic pressure of the standing water column in each tray. The temperature contour confirms elevated temperatures at the bottom surface, which increases the water molecules' motion and kinetic energy and in turn speeds up surface evaporation. The mass transfer rate contour quantifies how much vapor is generated at any point in the system, and this vapor generation rate matches the amount of water ultimately condensed at the cool sloped plates and collected as distillate, confirming that the vapor produced through evaporation is fully accounted for as clean water leaving through the outlet.

Geothermal Downhole Heat Exchanger (DHE) — Natural Convection ANSYS Fluent CFD SimulationDescriptionThis project simulates heat extraction from a geothermal reservoir using a single U-tube Downhole Heat Exchanger (DHE) — a U-shaped pipe installed inside a wellbore, through which a working fluid circulates to draw heat out of the ground. The case is a strong study in natural-convection-driven conjugate heat transfer: the heat path runs from the surrounding ground, through the borehole fluid, and finally into the water circulating inside the tube.The model consists of three coupled parts — the U-tube, the borehole, and the ambient geothermal reservoir — and represents a scaled version of a real field installation located roughly 200 m underground. In this simulation, the ground zone and U-tube are scaled to 6 m and 3.2 m depth respectively, with a 0.0875 m tube diameter inside a 0.35 m borehole, all contained within a 3 m ground cylinder.MethodologyThe geometry is created in Design Modeler, and a polyhedral mesh of approximately 1,750,000 cells is generated in ANSYS Meshing.The physics of the case centers on free (natural) convection. The solid ground temperature is defined as a linear function of depth using a Named Expression, so the borehole is heated from the bottom upward. Gravity is enabled, and the thermal conductivity and heat capacity of water are defined as temperature-dependent using the polynomial method — an essential detail, since the buoyancy forces driving the entire problem depend on capturing these property variations correctly.Turbulence is modeled with the Realizable k-ε model with standard wall functions, and the simulation is solved in steady-state form as a coupled solid–fluid heat exchange problem.AnalysisAt the end of the solution process, temperature and pressure contours along with velocity vectors are extracted for both the tube and borehole zones. The results show that convective heat transfer raises the tube outlet temperature to 305.47 K.The velocity vectors reveal the heat transfer mechanism clearly: a vortex forms at the bottom of the borehole, intensifying turbulence and enhancing heat transfer. Water near the hot wall warms, loses density, and rises; as it cools near the tube, it sinks again — completing the natural-convection loop that continuously feeds heat from the ground into the circulating tube water.By completing this project, you will learn to set up buoyancy-driven natural convection, define depth-dependent solid temperatures with Named Expressions, model temperature-dependent fluid properties, and run a coupled solid–fluid conjugate heat transfer simulation.