Aeroacoustic CFD Analysis: Sound Generation from Flow Over a Wedge
Aeroacoustic CFD Analysis: Sound Generation from Flow Over a Wedge
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A Sound Generation of flow over Wedge CFD analysis is a computer simulation that helps engineers understand how and why objects create noise when air flows past them. This field, known as aeroacoustics, is very important for designing quieter products. A wedge sound cfd study using ANSYS Fluent is a perfect way to see how a simple shape can become a major source of noise.
This report details an acoustic sound CFD Simulation that compares a wedge at two different angles. The analysis uses a powerful tool called the FW-H fluent acoustic model. This model is an industry standard for aeroacoustic CFD because it accurately calculates the sound waves created by unsteady flow, vortex shedding, and turbulence. The goal is to show how a small change in angle can lead to a big change in noise, providing essential data for reducing noise in aircraft parts, wind turbines, and even buildings. For comprehensive acoustic simulation tutorials and advanced aeroacoustic analysis techniques, explore CFDland’s acoustic simulation resources.
- Reference [1]: Mahato, Bikash, Naveen Ganta, and Yogesh G. Bhumkar. “Direct simulation of sound generation by a two-dimensional flow past a wedge.” Physics of Fluids9 (2018).

Figure 1: A schematic showing the 2D wedge geometry inside its circular computational domain, which is a common setup for aeroacoustic CFD simulations.
Simulation Process: Fluent-CFD Setup, A Transient FW-H Aeroacoustic Simulation
The simulation process for this wedge aeroacoustics study began with the creation of a 2D wedge geometry placed inside a large circular domain. Two distinct simulation cases were prepared to analyze the effect of the angle of attack (AOA): one case at 0° AOA and another at 10° AOA. A high-quality structured grid containing exactly 98,000 cells was generated. This mesh was made very fine near the wedge surfaces and in the wake region behind it, which is essential for correctly capturing the small, rapid pressure changes that create sound.
Inside ANSYS Fluent, a transient (time-dependent) solver was used because sound is, by its nature, an unsteady phenomenon. The inlet airflow was set to a speed of Mach 0.25. The key to this analysis was the activation of the Ffowcs Williams-Hawkings (FW-H) acoustic model. This model works by first solving the complex fluid flow around the wedge and then using that information to precisely calculate how sound waves are generated and travel away from it. To capture this sound, several virtual microphones, called acoustic receivers, were placed at different locations downstream.

Figure 2: The high-quality structured grid with 98,000 cells, showing the fine mesh density around the wedge to accurately capture the flow physics.

Figure 3: A diagram showing the location of the acoustic receivers downstream of the wedge, which are used to measure the sound pressure levels in the FW-H acoustic model.
Post-processing: Correlating Aerodynamics with Acoustic Noise Generation
The simulation results provide a complete engineering analysis, showing a powerful and direct link between the aerodynamic forces on the wedge and the amount of noise it produces. The data shows that increasing the angle of attack from 0° to 10° causes a dramatic and undesirable change in performance. From an engineering viewpoint, the analysis must start with the forces. The simulation calculated the following aerodynamic coefficients:
| Angle of Attack | Lift Coefficient (Cl) | Drag Coefficient (Cd) |
| 0° AOA | 0.0001 (Effectively Zero) | 4.4628562 |
| 10° AOA | 0.17515562 (Extremely High) | 7.5929939 (Extremely High) |
This data tells a clear story. At 0°, the forces are symmetric and manageable. At 10°, the lift and drag forces become enormous. The streamline and vorticity contours (Figures 4 and 7) explain why: at 10°, the flow can no longer follow the sharp angle of the wedge and separates from the surface. This massive flow separation creates a very large, chaotic, and turbulent wake. This wake is the engine for both the huge aerodynamic forces and the intense noise.

Figure 4: Vorticity contours showing flow patterns for 0° AOA (top) and 10° AOA (bottom) wedge cases

Figure 5: Velocity contours comparing flow over wedge at different angles of attack
This direct link is proven by the acoustic receiver data in Figure 6. At 0° AOA, the sound pressure levels (SPL) are very low, mostly in the negative dB range. This indicates a relatively quiet flow. However, at 10° AOA, the SPL values are dramatically higher, jumping up to around 70 dB. This is a massive increase in acoustic energy. The chaotic vortex shedding in the wake at 10° AOA creates large, rapid pressure fluctuations in the air, and these pressure fluctuations are precisely what we hear as sound. The spiky, irregular nature of the 10° AOA plots across a wide range of frequencies is characteristic of broadband noise, which is typical of highly turbulent flows. The most important achievement of this simulation is the clear, quantitative connection it establishes between a change in angle of attack, the resulting aerodynamic penalty, and the severe acoustic consequence. For a designer or manufacturer, this is critical information. It shows that even a small misalignment of a part (like a bracket on an airplane or a structural element on a building) can lead to both dangerously high structural loads and significant noise pollution. This FW-H Fluent acoustic analysis provides the precise data needed to design components with shapes and operating angles that minimize both drag and noise, leading to safer, quieter, and more efficient products.

Figure 6: Acoustic spectral analysis from FW-H model showing sound pressure levels at downstream receivers

Figure 7: A comparison of streamline patterns, which visually confirm the massive flow separation occurring on the wedge at 10° AOA.
We pride ourselves on presenting unique products at CFDLAND. We stand out for our scientific rigor and validity. Our products are not based on guesswork or theoretical assumptions like many others. Instead, most of our products are validated using experimental or numerical data from valued scientific journals. Even if direct validation isn’t possible, we build our models and assumptions on the latest research, typically using reference articles to approximate reality.
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