A Fan Noise Acoustics CFD Simulation Using Broadband Noise Source Model is a special computer model that predicts the sound a fan makes. This is a type of Aeroacoustics CFD Simulation, which studies noise created by airflow. This analysis is very important for making quieter products, like air conditioners (HVAC Noise CFD) or computers. An Acoustics Fluent simulation is done in two steps. First, we model the airflow around the fan. Second, we use that information to calculate the noise. For this, we use the Broadband Noise Source Model Fluent, which is good at predicting the “whooshing” sound of Turbulent Noise Generation.

• Reference [1]: Yadegari, Mehdi, et al. “Reducing the aerodynamic noise of the axial flow fan with perforated surface.” Applied Acoustics 215 (2023): 109720.

Simulation Process: Fluent Setup, Two-Step CFD and Acoustics Broadband Noise Modeling

This Fan Noise Acoustics Fluent analysis was a two-step process inside ANSYS Fluent. First, we performed a steady-state fluid dynamics simulation to understand the airflow. We created a 3D geometry with a rotating zone for the fan and a stationary zone for the housing. We used a polyhedral mesh to accurately model the flow. We used the MRF (Multiple Reference Frames) model to efficiently simulate the fan rotating at 2818 rpm. To capture the chaotic airflow, which is the source of the noise, we used the powerful SST k-ω turbulence model. After this first simulation was complete, we began the second step. We kept the fluid flow results and activated the Acoustics Model in Fluent. We chose the Broadband Noise Source Model. This smart model uses the turbulence data (like turbulent kinetic energy) from our first simulation to calculate where the sound energy is being created on the fan’s surfaces. Finally, we defined a “receiver” surface around the fan to listen to and measure the sound that travels away from the fan.

Figure 1: Polyhedra grid over 3D Axial Fan CFD Simulation

Post-processing: Acoustic Analysis, Locating Noise Sources and Predicting Sound Level

The acoustic power level contour is not just a contour; it is a map that shows an engineer exactly where the fan is shouting. The result is a powerful diagnostic tool. The analysis reveals that the noise is not created equally everywhere on the fan blades. Instead, the sound energy is highly concentrated, with the highest levels located at the blade tips and along the leading edge (the front edge) of each blade. This is where the engineering story begins. The tips are moving the fastest, and the leading edges are slicing into the air, creating the most intense and chaotic turbulence. This turbulence is the direct source of the broadband “whooshing” noise. We can see noise sources reaching up to -30 dB in these specific regions.

Figure 2: A plot of the acoustic power level on the fan blades, calculated by the Broadband Noise Source Model CFD, showing where the noise is generated.

This simulation lets us listen to the fan from afar. The Sound Pressure Level (SPL) contour shows how this noise source energy translates into the loudness we would actually hear. The analysis predicts a maximum sound level of 55 dB at a distance of 1 meter in front of the fan, which is a key performance metric. The contour also shows that the noise projects forward, in the direction of the airflow, which is typical for axial fans. For an engineer, this is the complete story: we can see the cause of the noise (the high turbulence at the blade tips shown in Figure 2) and the effect of that noise (the 65 dB sound level spreading from the fan shown in Figure 3). The most important achievement of this simulation is its ability to bridge the gap between aerodynamics and acoustics, not only predicting the final loudness of the fan but also visually pinpointing the exact geometric features—the blade tips and leading edges—that are the primary noise offenders. This gives engineers a clear roadmap for design changes to create a quieter, better product.

Figure 3: Velocity Distribution of  Fan Noise Acoustics CFD Simulation Using Broadband Noise Source Model