Wall Wavy Motion CFD Simulation, Dynamic Mesh, ANSYS FluentDescriptionThis project simulates flow behavior within a channel featuring a non-stationary, wavy bottom wall using ANSYS Fluent's dynamic mesh capabilities. The 2D channel geometry was designed in Design Modeler and meshed in ANSYS Meshing using an unstructured grid, with mesh quality specifically optimized to support the dynamic deformation required by this simulation.MethodologyThe dynamic mesh model governs the wavy wall's motion, implemented through a Grid Motion UDF that prescribes the wall's oscillating displacement over time. The mesh zone directly above this non-stationary wall was assigned the Deforming option, allowing it to continuously adjust as the wall moves through its wave cycle. Given the inherently time-dependent nature of this wave-induced flow, the simulation was configured as transient, with solver settings and time-stepping strategy tuned to maintain both accuracy and stability throughout the deforming-mesh solution process.ConclusionThe results capture how the channel's continuously changing cross-section — driven by the wavy wall's motion — shapes the resulting velocity and pressure fields over time. Time-varying pressure and velocity contours, along with accompanying animations, reveal the close coupling between the wall's oscillation and the flow's evolving behavior: as the wall's wave motion narrows and widens the channel cross-section, velocity and pressure respond correspondingly, producing a clear, time-dependent flow pattern directly tied to the prescribed wall movement. These results illustrate the core mechanics of dynamic-mesh-driven wave propagation in a bounded channel, providing a foundation for analyzing similar non-stationary boundary problems in hydraulic and fluid-structure interaction applications.

Nanofluid Flow in a Wave Sine Channel, Heat Transfer Analysis, ANSYS Fluent CFD Simulation TrainingDescriptionThis project simulates the wave motion of a nanofluid within a sinusoidal channel using ANSYS Fluent, with the nanofluid defined as Al₂O₃-water containing nanoparticles at a 1% volume fraction. The thermophysical properties of this nanofluid mixture were derived from standard nanofluid property equations, using the base thermophysical properties of both water and the Al₂O₃ nanoparticles as inputs.The nanofluid enters the channel at 300 K. Due to the channel's wavy geometry, the horizontal velocity of the incoming flow varies as a function of vertical position, defined through a custom velocity profile implemented as a UDF. Thermally, the channel's lower wall was assigned a constant heat flux of 320 W/m², while the upper wall was held at a constant temperature of 320 K.The 2D geometry was designed in Design Modeler, representing a sinusoidal channel 4 m long and 1 m wide, with a wavelength of 2 m and peak-to-trough height of 0.4 m. The domain was meshed in ANSYS Meshing using a structured grid totaling 21,300 elements.MethodologySeveral assumptions were applied to the simulation: a pressure-based solver was used, the simulation was run under steady-state conditions, and gravitational effects were excluded.Key simulation settings included:Viscous model: Laminar, with the energy equation enabledBoundary conditions: Velocity inlet defined via the UDF-based velocity profile at 300 K; pressure outlet at 0 Pa gauge pressure; upper wall held at a constant 320 K; lower wall assigned a constant heat flux of 320 W/m², both stationarySolution methods: Coupled pressure-velocity coupling, second-order pressure discretization, and second-order upwind schemes for both momentum and energyInitialization: Standard method, with 0 Pa gauge pressure, 0.0015 m/s x-velocity, 0 m/s y-velocity, and 300 K temperatureConclusionResults include 2D contours of temperature, pressure, and velocity throughout the channel, along with plots tracking pressure and velocity variation along a hypothetical horizontal line through the channel's midline. These results characterize how the sinusoidal wall geometry, combined with the nanofluid's enhanced thermal properties, shapes the resulting flow acceleration and heat transfer pattern as the nanofluid moves through the wavy channel structure.

Diaphragm Pump CFD Simulation, ANSYS Fluent TrainingDescriptionThis project simulates a diaphragm pump using ANSYS Fluent. A pump is a mechanical device that transfers liquid from one location to another, drawing mechanical energy from an external source such as a motor and transferring it to the fluid passing through, thereby increasing the fluid's energy as it exits the pump.Pumps transfer this energy through either dynamic or displacement methods, dividing them into dynamic (non-positive displacement) pumps and positive displacement pumps — the latter further split into rotary types (gear, lobe, vane) and reciprocating types (piston, diaphragm). A diaphragm pump falls into this reciprocating category, using a flexible composite membrane that moves up and down over the working fluid: as the membrane rises, fluid is drawn in through the intake valve, and as it descends, fluid is pushed out through the outlet valve.This project models the water flow inside a diaphragm pump, focusing on capturing the membrane's reciprocating motion and its effect on the surrounding flow. Since this motion continuously alters the fluid domain, the computational mesh must deform correspondingly over time.The geometry was designed in Design Modeler, representing the pump's internal space along with the moving membrane, and meshed in ANSYS Meshing using an unstructured grid totaling 222,986 cells.MethodologySince a moving boundary or deforming zone is present, the dynamic mesh model was applied throughout the simulation. Here, the moving wall — the membrane — generates a wave-like motion that deforms the mesh over time, defined through a UDF implementing the Grid Motion approach to prescribe this wavy wall behavior.Given the membrane's reciprocating motion as a rigid body, the mesh region adjacent to it was assigned the Deforming option to accommodate this continuous change. Since the resulting fluid behavior is inherently time-dependent, the simulation was run using an unsteady (transient) solver.ConclusionResults include pressure and velocity contours, along with corresponding animations capturing how these fields evolve as the membrane moves through its cycle. The results confirm that pressure and velocity fluctuate continuously in direct response to the membrane's reciprocating motion — this motion drives fluid suction through the intake valve during the upstroke and compression toward the outlet valve during the downstroke, reproducing the diaphragm pump's core operating cycle.

Speaker Sound Generation and Propagation Inside a Pipe CFD Simulation, ANSYS FluentDescriptionSound generation in a speaker involves several sequential steps. An incoming electrical signal is sent to a coil, generating a fluctuating magnetic field that interacts with a permanent magnet's field, causing the coil to move rapidly back and forth. This coil is attached to a diaphragm, which displaces the surrounding air as it moves — pressurizing air as it moves forward and expanding it as it moves backward — generating pressure waves. These waves propagate through the air, and when they fall within the frequency range of human hearing, they are perceived as sound. The resulting sound's frequency matches that of the electrical input driving the coil, while its amplitude (loudness) depends on how far the diaphragm physically displaces.This project models a speaker diaphragm with a maximum displacement of 2 mm, vibrating in a sinusoidal pattern at 500 Hz. The diaphragm's resulting velocity profile was derived from this displacement function and implemented as a boundary condition through a custom UDF hooked into the dynamic mesh solver.Four receiver points were defined within the domain to track acoustic results at increasing distances from the speaker. The geometry was designed in SpaceClaim and meshed in ANSYS Meshing using a structured mesh totaling 687,500 elements.MethodologyTurbulence was modeled using the standard k-ε model. Diaphragm motion was captured using dynamic mesh: at each time step, the solver calculates the diaphragm's updated position and remeshes the surrounding domain using smoothing and layering methods to accommodate the moving boundary. The simulation ran as unsteady, using a time step of 0.001 s over 1000 total time steps.ConclusionResults include pressure and turbulence kinetic energy contours across the domain's central plane, along with an animation showing the evolving pressure field over time. Static pressure was extracted at each of the four receiver points, and the resulting Sound Pressure Level plots confirm that the generated sound's frequency matches the diaphragm's vibration frequency exactly at 500 Hz.The results also show a clear amplitude trend: as distance from the speaker increases across receivers 1 through 4, the amplitude of the pressure fluctuations — and correspondingly, the loudness of the sound — steadily decreases, consistent with the expected attenuation of sound pressure as it propagates downstream through the domain.

Falling Objects into Water CFD Simulation, Dynamic Mesh, ANSYS Fluent TrainingDescriptionThis project simulates the fluid flow generated by two cubes falling into water using the dynamic mesh method in ANSYS Fluent. The 2D geometry was designed in Design Modeler, with two cubes positioned within a square domain, set to fall into the underlying fluid under gravitational acceleration. The domain was meshed in ANSYS Meshing, totaling 8,727 elements, with a transient solver enabled given the dynamic mesh approach required for this problem.MethodologyIn problems where mesh cell location and shape change over time, the dynamic mesh model is essential to prevent severe deterioration in element quality. Smoothing and remeshing methods regenerate higher-quality elements as the original mesh becomes distorted and unsuitable for continued calculation.The two cubes begin at rest in the air above the domain; once the simulation starts, they fall and collide with the free surface separating water and air, with this two-phase behavior captured using the VOF multiphase model. A UDF governs the cubes' motion toward the water surface based on gravitational acceleration, while turbulence is resolved using the standard k-epsilon model.ConclusionResults include 2D contours of velocity, pressure, turbulent viscosity, and streamlines throughout the domain. As the cubes move downward and generate a sloshing effect, pressure rises progressively along their path of movement, peaking sharply at the tank's corners and at the cubes' own sharp edges, while dropping to a minimum along the cubes' vertical faces — a direct result of flow separation induced by their motion through the fluid.The kinetic energy contour further reveals elevated average kinetic energy concentrated around the cubes, driven by the vortices generated as they move through the fluid — a clear sign of increased turbulence resulting from the falling motion. These wake regions are also clearly visible in the accompanying streamline and vector plots, illustrating how the cubes' descent reshapes the surrounding flow field.

Oscillatory Wave and its Effect on Fin Motion, ANSYS Fluent CFD TrainingDescriptionThis project simulates the rotational motion of a fin within a two-phase flow field, driven by an oscillatory wave generated through ANSYS Fluent.The 2D geometry was designed in Design Modeler, divided into three main regions: structured, unstructured, and stationary. Meshing was carried out in ANSYS Meshing, totaling 120,049 elements. An unstructured mesh was applied specifically in the region surrounding the fin, since this area undergoes deformation through the dynamic mesh process and requires high flexibility to accommodate remeshing, while the remaining regions retain a structured mesh.The model is inherently unsteady, since it simulates the fin's rotational motion under a time-dependent oscillating fluid wave. Gravitational effects were included at 9.81 m/s² along the y-axis, given their influence on the torque acting on the fin.MethodologyThe two-phase flow was modeled using the VOF model, with air as the primary phase and water as the secondary phase, with no interaction or mass transfer between them. The motion of a rigid wall and its attached boundaries generates an oscillatory wave within the domain, which applies compressive force and shear stress to the fin mounted on the domain floor — causing the fin to rotate about its vertical axis as a rigid body.Since the problem requires boundary displacement, a dynamic mesh technique was used to capture the fluid flow, with a UDF defining the reciprocating motion of the scaffold wall responsible for generating the waveform. The simulation ran for 100 seconds with a time step of 0.001 s.Dynamic mesh smoothing was applied using a spring constant of 0.7, 500 iterations, and a convergence tolerance of 0.001, combined with the remeshing method using local cell sizing; spring-based smoothing alone was not used. The fin is constrained to a single degree of freedom (1-DOF), rotating about the z-axis around its pivot point, exhibiting reciprocating motion driven by wave impact. The moment of inertia applied to the fin was set to 0.1147 kg·m², equivalent to that of a rotating rod about its endpoint (I = 1/3·mL²).ConclusionThe results include 2D contours of pressure, velocity, and the volume fraction of air and water, along with pathlines captured at t = 2s. By enabling the write motion history option within the 6-DOF definition settings, the fin's x-y position and angular orientation were recorded over time as a dataset, producing a graph of the fin's angular displacement across the full 22.5-second simulation window.

Submarine Movement in Water by Dynamic Mesh (1-DOF), ANSYS FluentDescriptionThis simulation models the motion of a submarine in water using the Dynamic Mesh method in ANSYS Fluent, with a computational domain containing both air and water phases at a defined water level, with the submarine positioned within this domain.The submarine geometry was designed first, followed by a computational domain incorporating two-phase (air-water) flow around it. Both were modeled in 3D using Design Modeler. The domain includes distinct inlet and outlet sections, with symmetry conditions applied to the four surrounding faces.Meshing was carried out in ANSYS Meshing using an unstructured mesh totaling 316,846 elements.MethodologySince the submarine moves within the computational domain, affecting the surrounding grid elements, the mesh requires continuous, time-dependent updates based on the displacement occurring at adjacent mesh boundaries. This is achieved through the dynamic mesh model, applying smoothing and remeshing methods, with the submarine's wall defined as a Rigid Body.The submarine is constrained to a single degree of freedom (1-DOF), permitted to rotate only about its central axis (x-axis), with no translational or additional rotational motion. This rotational behavior is defined through a UDF, with rotational velocity varying between +1.5 rad/s and -1.5 rad/s over the 0–3 second simulation window.The rigid body settings also require specifying the spatial coordinates of the submarine's center of gravity and its axis of rotation.Since the domain contains two phases, the VOF multiphase model is applied, with air occupying the upper region and water the lower region. To represent the submarine operating in open sea conditions, wave behavior is introduced via the open channel wave boundary condition — incoming water enters at an average velocity of 10 m/s along the horizontal (x-axis), with the wave trough set at -10.16 m and its crest at 0 m. Inlet airflow enters at atmospheric pressure (zero relative pressure), with air discharged at atmospheric pressure as well.Given the dynamic mesh foundation of this model, the simulation is run as a transient (time-dependent) case, spanning 3 seconds with a time step of 0.01 seconds — necessarily unsteady due to the dynamic mesh method employed.ConclusionThe results include 2D contours of velocity and volume fraction for both water and air phases, along with 2D pathlines around the submarine — captured on a plane perpendicular to the submarine's horizontal axis (parallel to the Y-Z plane) at multiple points throughout the simulation.Consistent with the defined UDF, the submarine exhibits reciprocating rotational motion about its central axis, alternating between clockwise and counterclockwise rotation over the course of the simulation.

Sloshing Tank, ANSYS Fluent CFD Simulation TrainingDescriptionExperimental and numerical studies consistently demonstrate the importance of fluid sloshing within a tank on the maneuverability of floating vessels such as ships and boats. Several key laboratory studies inform this area of research, including measurements of sloshing dynamics within a tank, experimental-statistical analysis of sloshing wave impact loads on shell tank models, verification of numerical sloshing results against experimental data from scaled reservoir sections at different filling heights, investigation of long-term sloshing pressures accounting for impact-induced vibration, and experimental studies of pressure distribution from liquid sloshing in rectangular tanks.The computational domain represents a tank containing LNG fuel and air, incorporating several rows of internal joints and walls designed to restrict fluid movement. This reduces friction between fluid layers, since the inertia of fluid moving within the tank can otherwise affect the stability of the fuel carrier vehicle.The 2D tank geometry was modeled in Design Modeler, measuring 1 m in length and 0.7 m in width. Six rows of internal dividers, each 0.35 m high and 0.04 m thick, separate the fluid layers, with the geometry segmented to support a structured mesh. Since ANSYS Fluent relies on the finite volume method, mesh quality is critical; a structured mesh was accordingly generated for the tank using ANSYS Meshing.MethodologyThe simulation was set up using a pressure-based solver with absolute velocity formulation, run as a transient case with a 0.005 s time step. Gravity was enabled at -9.81 m/s² in the Y-direction, while the energy equation was disabled.Tank motion was defined through a UDF applying an oscillating zone velocity along the X-direction following a sinusoidal function, with the rotation axis fixed along Z. All walls were assigned a no-slip condition, and the reference pressure point was set at X = 0.00 m, Y = 0.25 m.The VOF multiphase model was used, with air as the primary phase and water as the secondary phase, applying implicit formulation, sharp interface modeling, and implicit body force, alongside an enabled level-set method for improved interface tracking; open channel flow was disabled. A surface tension coefficient of 0.0725 N/m was defined for the air-water interaction.Solution methods included SIMPLE for pressure-velocity coupling, PRESTO! for pressure interpolation, and QUICK schemes for both momentum and level-set discretization, with a compressive scheme applied to VOF implementation. The domain was initialized uniformly at zero, followed by a patch applied over the region X: -10 m to +10 m, Y: 0 to 0.25 m, setting static pressure as ρ_w·g·(1 − y/H_w) and a water volume fraction of 1.0. Static pressure was monitored throughout the simulation at a point located at Y = 0.0525 m.ConclusionThe simulation captures the oscillatory sloshing behavior of fluid within the tank as it responds to the applied motion, tracking the resulting pressure fluctuations at the monitored point over time. These results characterize how internal baffles and fluid inertia influence sloshing loads — information directly relevant to assessing structural and stability impacts on the fuel carrier vessel under realistic operating motion.

Shell and Tube Heat Exchanger, PCM Thermal Storage System, Paper Numerical Validation, CFD Simulation by ANSYS FluentDescriptionThis project simulates the solidification and melting of a phase change material (PCM) within a shell and tube heat exchanger, based on the reference article "Experimental and computational evolution of a shell and tube heat exchanger as a PCM thermal storage system," with results compared and validated against both the experimental and numerical results reported in the paper.Phase change materials are organic compounds capable of absorbing and storing large amounts of latent thermal energy. This energy storage occurs during the phase transition itself: as the material melts from solid to liquid, it absorbs heat from its surroundings (producing a cooling effect), while as it solidifies from liquid back to solid, it releases that stored heat back into the environment (producing a heating effect).The PCM used in this simulation is RT50-type paraffin, defined with a density of 820 kg/m³, specific heat capacity of 2000 J/kg·K, and thermal conductivity of 0.2 W/m·K. Its viscosity was defined as temperature-dependent, implemented through a UDF using an exponential function of temperature.The heat exchanger itself is constructed from copper, with water flowing through the inner tube at a mass flow rate of 0.008318 kg/s and a temperature of 343.15 K, while the surrounding shell section is filled with the PCM.Geometry & MeshThe 3D geometry was designed in Design Modeler, representing a shell and tube heat exchanger with an inner tube wall thickness of 0.0025 m. The pipe spans 1 m in length, with inner and outer radii of 0.011 m and 0.0425 m, respectively. Given the pipe's symmetrical structure, only half the geometry was modeled to reduce computational cost.The domain was meshed in ANSYS Meshing using a structured grid totaling 169,171 elements.MethodologyThe Solidification and Melting model was used to capture the PCM's phase-change behavior, defined with a solidus temperature of 317.2 K, a liquidus temperature of 327.3 K, and a latent heat of fusion of 170,320 J/kg.ConclusionA graph tracking the temperature evolution of the PCM-filled shell section over the course of a complete melting cycle was extracted and compared directly against Figure 8 of the reference article, which includes both experimental measurements and numerical CFD results. This comparison confirmed that the current simulation achieves acceptable accuracy relative to both the numerical and experimental results reported in the paper.Additional 2D and 3D contours of pressure, temperature, and liquid mass fraction were also obtained, providing a detailed view of how the PCM transitions from solid to liquid throughout the shell as it absorbs heat from the circulating hot water in the inner tube.

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.