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.

Acoustic CFD Simulation (LES) of Airflow over Cylinders in 4 Different Positions, ANSYS Fluent TrainingDescriptionThis project simulates airflow acoustics over cylinders arranged in four different positions using Large Eddy Simulation (LES) in ANSYS Fluent. Acoustics is the branch of science concerned with mechanical waves in gases, liquids, and solids — encompassing vibration, sound, ultrasound, and infrasound — and covers the production, control, transmission, reception, and effects of these waves.The domain was meshed in ICEM CFD using a structured mesh, with each configuration file containing approximately 2,000,000 elements and a boundary layer mesh applied around the cylinders. Given the nature of this problem, the simulation was run using a transient solver.MethodologyThis project simulates sound pressure waves generated around cylinders across four distinct positional configurations. Sound waves within a fluid arise from the vibration and reciprocating motion of fluid layers — as one layer of air moves forward, the adjacent layer is pushed forward in turn before returning to its original position. These reciprocating movements continue until the energy within the flow dissipates, and audible sound is produced once this oscillation exceeds roughly 16 cycles per second.Air density was defined at 1.225 kg/m³, with an inlet velocity of 69.2 m/s. Flow turbulence was resolved using the LES Smagorinsky model, while acoustic behavior was captured using the Ffowcs Williams-Hawkings equations. The SST k-omega model was additionally used to solve the turbulent flow equations supporting the broader simulation setup.ConclusionResults include 2D pressure contours across each of the four cylinder configurations, along with Sound Pressure Level plots extracted at several defined monitoring points: a lower point at (0, -0.15 m, 0), a first point at (0.4, 0, 0), and a second point at (0.7, 0, 0), with a 100 mm spacing between cylinder centers in both the X and Y directions.The results show a clear trend: sound pressure level increases the closer a monitoring point sits to the cylinder, confirming that the cylinder surface acts as the dominant near-field source of the generated acoustic pressure fluctuations.

Gun Muffler CFD Simulation: Acoustic and Dynamic Mesh Analysis by ANSYS FluentDescriptionThis project simulates and analyzes the acoustic performance of a gun muffler using ANSYS Fluent, comparing gunshot noise characteristics with and without the muffler installed. The study combines dynamic mesh techniques with the Broadband acoustic model to capture both the bullet's motion through the barrel and muffler, and the resulting sound wave propagation.The gun and muffler geometry — including the barrel, bullet, and muffler components — was built in SpaceClaim, with the muffler specifically designed to reduce noise by altering the sound wave as it passes through. The domain was meshed with fine resolution concentrated in regions expecting high pressure and velocity gradients, particularly around the muzzle and within the muffler itself, to accurately capture the sound wave's interaction with the muffler's internal geometry.MethodologyThe bullet's movement through the barrel and muffler was captured using dynamic mesh, while the Broadband acoustic model captured the gunshot's acoustic signature and evaluated the muffler's noise suppression effectiveness. Appropriate inlet and outlet boundary conditions were set to represent the firing event and subsequent sound wave propagation, with a pressure-based solver run under transient conditions to capture the inherently dynamic nature of the problem.ConclusionThe results reveal a clear contrast between the muffled and unmuffled cases. Without the muffler, the simulation showed substantially higher sound pressure levels, reflecting significant noise generation from the gunshot; with the muffler installed, sound pressure levels dropped noticeably, confirming its effectiveness at noise suppression.Acoustic power level results reinforce this: with the muffler, levels peak at approximately 129 dB near the muffler outlet before dissipating to around 90 dB further downstream, while the unmuffled case (modeled as a simple cylinder) peaks considerably higher at 133 dB and remains elevated above 100 dB well downstream — a meaningfully wider and more persistent noise footprint.Pressure fluctuation results follow the same pattern. With the muffler, pressure peaks reach roughly 11,000 Pa near the outlet before settling back toward atmospheric pressure downstream. Without the muffler, pressure swings are far more extreme, reaching positive peaks above 13,600 Pa and negative swings down to -12,400 Pa, with these fluctuations persisting much further downstream.Together, these results confirm that the muffler substantially reduces both the acoustic power level and the amplitude of pressure fluctuations generated by the gunshot, quantifying its effectiveness as a noise suppression device. The dynamic mesh and Broadband acoustic modeling approach successfully captured the complex interaction between the bullet, the muffler geometry, and the resulting sound field, providing a solid basis for further work — such as optimizing muffler geometry or exploring alternative materials and configurations for enhanced noise reduction.

Ducted Fan: Noise and Thrust CFD Study, ANSYS FluentDescriptionThis project simulates a ducted fan installed within a room, investigating both its acoustic behavior and thrust performance. Airflow enters the room through a doorway at 0.5 m/s, while an outlet is positioned on the wall where the ducted fan is mounted, with the fan itself rotating at 1000 rpm.The 3D geometry was designed in Design Modeler, representing a 2×3 m rectangular room with a 2.5 m ceiling height and a 30 cm diameter fan. The domain was meshed in ANSYS Meshing, initially generating a tetrahedral mesh that was then converted to polyhedral elements to reduce element count and computational cost, totaling 699,432 elements.MethodologyGravitational acceleration was included in the negative Y-direction at 9.81 m/s², with the k-epsilon Realizable model employed to capture the expected wake structures and turbulence around the fan. A dedicated rotating zone was defined around the fan using the Moving Reference Frame (MRF) approach, while the Ffowcs Williams-Hawkings (FW-H) acoustic model was used to predict the resulting acoustic effects.ConclusionTwo sound receivers were placed within the room to evaluate the fan's noise impact — one positioned directly in front of the fan (Receiver 1), and another near the room's entrance by the door (Receiver 2). Flow contours show air entering the domain at 0.5 m/s, forming a wake around the fan zone before exiting the domain, with the duct itself acting as a natural silencer that limits how far the fan's sound propagates.As a result, while the sound pressure level remains high at Receiver 1 (closest to the fan), it drops to an acceptable range by Receiver 2, posing no concern for occupants near the entrance. This is confirmed by the A-weighted sound pressure level, which peaks at 80 dB — comfortably below the 120 dB threshold typically associated with harmful noise exposure. The simulation also reports a fan thrust force of 54.113455 N.

Acoustic in a Turbojet Intake Fan CFD SimulationDescriptionThis project simulates airflow inside a turbojet, examining the acoustic waves and sound generated within it using ANSYS Fluent. The incoming airflow is defined at a pressure of 85,416.92 Pa and a temperature of 283.9524 K, derived from the relevant governing equations.The model includes a turbojet fitted with a fan at its inlet, rotating at 2000 rpm about the X-axis. A dedicated airflow region surrounding the fan was defined and modeled using the Moving Reference Frame (MRF) approach to capture this rotational motion. The turbojet itself moves through the air at Mach 0.5 — since this exceeds the commonly used Mach 0.3 threshold for treating flow as compressible, the simulation accounts for compressibility accordingly, with a density-based solver applied and air density defined via the ideal gas law. The surrounding airflow domain was assigned a pressure far-field boundary condition at Mach 0.5.The 3D geometry was built in Design Modeler, consisting of the turbojet body with its internal fan positioned within a cylindrical computational domain representing the surrounding airflow. The region immediately around the fan was defined as an independent computational zone, allowing the fluid rotation induced by the fan to be captured through the frame motion method, while the full surrounding cylindrical domain carried the pressure far-field boundary condition. The domain was meshed in ANSYS Meshing using an unstructured grid totaling 3,723,166 elements.MethodologyAcoustic behavior was modeled using the Broadband Noise Sources model, with reference values set to match standard air properties: a reference density of 1.225 kg/m³, a reference sound speed of 340 m/s, and a reference acoustic power of 1×10⁻¹² W.ConclusionResults include contours and vector fields for velocity, pressure, temperature, Acoustic Power Level (dB), and Surface Acoustic Power Level (dB) throughout the domain, offering detailed insight into the turbojet's acoustic behavior. As air strikes the fan and its surrounding wall, the resulting acoustic parameters become most clearly defined in the region immediately downstream of the fan, with the Surface Acoustic Power Level concentrated along the fan surface itself — identifying it as the dominant noise source in this system.Plots of Acoustic Power Level and Surface Acoustic Power Level taken along the domain's centerline further clarify the precise magnitude and distribution of acoustic activity downstream of the fan, providing a clear quantitative picture of how the fan's rotation drives the turbojet's overall acoustic signature.

Acoustic (Broadband) Investigation on a HAWT, ANSYS Fluent CFD Simulation TutorialDescriptionThis project investigates the acoustic performance of a horizontal axis wind turbine (HAWT), examining the noise it generates at multiple points throughout its surrounding domain. The simulation runs in a transient state using ANSYS Fluent, with the turbine rotating at 72 rad/s about its horizontal axis while an incoming air stream approaches at 15 m/s. Several monitoring points positioned both upstream and downstream of the turbine were selected for detailed noise investigation.The acoustic results from this project are directly comparable to the companion study, "Acoustic (FWH) Investigation on a HAWT, ANSYS Fluent CFD Simulation Tutorial", which solves the same underlying model using the Ffowcs Williams-Hawkings (FWH) method instead — giving learners a direct side-by-side comparison of two distinct aeroacoustics prediction approaches applied to identical turbine conditions. Setting up this Broadband approach requires creating monitor points through the Surface–Create–Point tab under the Domain menu, then defining corresponding plots in the Report Definitions tab so acoustic quantities can be tracked transiently at each time step.The geometry was designed in Design Modeler and meshed in ANSYS Meshing using tetrahedral elements, totaling 2,696,011 elements.MethodologyAcoustic behavior was modeled using the Broadband Noise Source model, while turbine rotation was captured using the Moving Reference Frame (MRF) method applied within the Cell Zone Conditions. Turbulence was resolved using the k-ω SST model.ConclusionThe acoustic results extracted at each defined monitoring point throughout the domain include Acoustic Power Level (dB), Surface Acoustic Power Level (dB), Power Spectral Density, and Lilley's self-noise source, among other parameters. Results show Acoustic Power Level increasing significantly along the turbine's blade surface with distance from the hub, tracking the corresponding rise in local velocity magnitude toward the blade tip.These results can be directly compared against the companion FWH-based study referenced above, since both solve the identical turbine model using different acoustic prediction methods. The full set of resulting contours, plots, pathlines, and FFT spectra are provided as accompanying figures, offering a comprehensive view of the turbine's acoustic signature across the surrounding domain.

Acoustic (FWH) Investigation on a HAWT, ANSYS Fluent CFD Simulation TutorialDescriptionThis project investigates the acoustic performance of a horizontal axis wind turbine (HAWT), examining the noise it generates at multiple points throughout its surrounding domain. The simulation runs in a transient state using ANSYS Fluent, with the turbine rotating at 7 rad/s about its horizontal axis while an incoming air stream approaches at 15 m/s. Several monitoring points positioned both upstream and downstream of the turbine were selected for detailed noise investigation.The acoustic results from this project are directly comparable to the companion study, "Acoustic (Broadband) Investigation on a HAWT, ANSYS Fluent CFD Simulation Tutorial", which solves the same underlying model using the Broadband Noise Source method instead — giving learners a direct side-by-side comparison of two distinct aeroacoustics prediction approaches applied to identical turbine conditions. In this FWH-based setup, monitoring points are defined through the Acoustic Model–Define Receivers tab, while the noise source itself — the turbine's blade surface — is selected through the Acoustic Model–Define Sources tab.The geometry was designed in Design Modeler and meshed in ANSYS Meshing using tetrahedral elements, totaling approximately 2,500,000 elements.MethodologyAcoustic behavior was modeled using the Ffowcs Williams-Hawkings (FWH) acoustic model, while turbine rotation was captured using the Moving Reference Frame (MRF) method applied within the Cell Zone Conditions. Turbulence was resolved using the k-ω SST model.ConclusionThe acoustic results extracted at each defined receiver point include Surface dpdt RMS, static pressure, and sound pressure level (dBA), among other parameters. Results show the Surface dpdt RMS parameter increasing toward the blade edges farther from the hub, consistent with the higher local velocity magnitude and stronger interaction with the incoming wind flow in those regions.These results can be directly compared against the companion Broadband-based study referenced above, since both solve the identical turbine model using different acoustic prediction methods. The full set of resulting contours, plots, pathlines, and FFT spectra are provided as accompanying figures, offering a comprehensive view of the turbine's acoustic signature across the surrounding domain.

Francis Turbine Acoustics Analysis, ANSYS Fluent CFD Simulation TrainingDescriptionFrancis turbines are a type of water turbine capable of harnessing both kinetic and potential energy simultaneously for power generation, owing to the specific arrangement of their blades. Water flows into the turbine's spiral chamber, where the circular arrangement of the blades requires the incoming fluid to adopt a rotational flow pattern as it collides with them, improving overall operational efficiency. This rotational flow is then directed onto the turbine runner blades at a defined flow rate, driving their rotation and producing the desired mechanical work, with water ultimately exiting the runner blades in an axial direction.This simulation models water entering the turbine's inner chamber at a mass flow rate of 1.996 m/s, with the runner blades rotating at 158 rpm.The geometry was designed in Design Modeler around two main components: fixed walls carrying stationary vanes set at fixed angles, and moving walls carrying the rotating runner blades. The domain was meshed in ANSYS Meshing using an unstructured grid totaling 4,914,404 elements, with finer mesh resolution applied near the blade surfaces to capture the more complex local flow behavior.MethodologyBlade rotation within the chamber, and the resulting rotational flow field around the blades, was captured using the Moving Reference Frame (MRF) approach — the water flow region surrounding the blades is treated as rotating relative to the blades themselves, while the blades are assigned zero rotational speed relative to this rotating reference frame. Acoustic behavior was modeled using the Broadband Noise Sources model.ConclusionSince this simulation builds on an established turbomachinery configuration already characterized in prior hydraulic analysis, the acoustic investigation here proceeds directly from those same flow settings. The results show that the rotating runner blades contribute the larger share of sound generation within the system, exhibiting notably higher acoustic power in the corresponding contour compared to the stationary components.The linearized Euler equations' contour further illustrates how sound propagates through the space between the rotor and stator, offering insight into the acoustic wave transmission pathway within the turbine's internal geometry — information directly relevant to understanding and potentially mitigating turbine noise in real-world hydroelectric installations.

Pelton Turbine, Acoustic Analysis, ANSYS Fluent CFD SimulationDescriptionThis project simulates a Pelton turbine under acoustic analysis using ANSYS Fluent. A Pelton turbine is a hydraulic turbine that harnesses the energy of pressurized water to rotate a wheel fitted with cup-shaped blades, converting that energy into mechanical power.Sound generation in mechanical equipment is generally considered an undesirable byproduct, arising from the propagation of sound waves near surfaces. Acoustic analysis provides a way to investigate sound sources and noise propagation power across various systems, including rotating equipment and turbomachinery such as this turbine.The 3D geometry was modeled in Design Modeler, representing the interior of a closed chamber housing the Pelton turbine. The domain was meshed in ANSYS Meshing, generating approximately 4,136,000 cells.MethodologyAcoustic behavior was captured using the Broadband Noise Sources method, which estimates noise generation and predicts acoustic power levels emanating from the identified sound sources. Turbine rotation was represented using the Moving Reference Frame (MRF) approach, applying rotational motion to the fluid region surrounding the turbine body; since the simulation was run under steady-state conditions, this rotation was implemented through the Frame Motion tool at a specified rotational speed.ConclusionThe results capture both the fluid flow behavior and the resulting acoustic characteristics. The acoustic power level contour on the turbine body — representing the sound power, in decibels, generated as the surface interacts with the fluid — shows the highest acoustic power levels concentrated on the turbine blades themselves.This pattern aligns closely with the turbulent intensity contour, which shows the same trend: wherever turbulent intensity is higher, acoustic power level rises correspondingly. Pressure and velocity contours around the turbine body further reinforce this relationship, with the highest pressure and velocity values also concentrated near the turbine surface — consistent with the turbine body being the dominant source of sound generation in this system.Together, these consistent, physically coherent patterns across the acoustic, turbulence, and flow results confirm that the simulation was performed correctly and accurately captures the turbine's acoustic behavior.

Thermoacoustic Analysis in Combustion Chamber, CFD Simulation TutorialDescriptionThis project, covering non-premixed combustion and acoustics together, investigates a thermoacoustic phenomenon within a combustion chamber using ANSYS Fluent. In thermoacoustic systems, heat is converted into sound waves, which can then be harnessed for tasks such as pumping heat or generating electricity. Since the process involves no moving parts, it offers a reliable, low-maintenance approach to energy conversion.Methane and oxygen enter the domain through separate inlet boundaries at mass flow rates of 0.001 kg/s and 0.025 kg/s, respectively, mixing and combusting within the chamber. This simulation extracts both the Acoustic Power Level (dB) and Surface Acoustic Power Level (dB) using the steady-state acoustic model available in ANSYS Fluent — the former measuring total sound power, and the latter measuring sound power per unit surface area. The geometry was built in SpaceClaim, with the mesh generated in ANSYS Meshing.MethodologyCombustion was modeled using the Non-Adiabatic, Non-Premixed Combustion model, which accounts for heat loss occurring during combustion — reflecting the reality that some generated heat escapes to the surroundings rather than remaining fully contained. This makes the model more representative of practical scenarios where such losses can't be neglected. Acoustic behavior was captured using the Broadband Noise Source model, which predicts the broadband noise generated by turbulent flow within the CFD simulation.ConclusionThe extracted results include contours of several key parameters. The fuel's mass fraction shows it entering the domain from the center of the inlet plate, while air — defined with a 0.23 oxygen mass fraction and the remainder nitrogen — enters the surrounding zone around the fuel inlet. Mass fraction contours of the combustion reaction products are similarly visible throughout the domain.Acoustic results include the Surface Acoustic Power Level across the chamber walls and the Acoustic Power Level across a plane defined at the chamber's center. The maximum Surface Acoustic Power Level reached 73.56 dB, while the corresponding Acoustic Power Level value was somewhat lower, at 62.93 dB — illustrating how combustion-driven sound generation varies between the chamber's bounding surfaces and its interior flow field.