A Ceiling Fan Noise CFD analysis is an important engineering tool used to understand and reduce unwanted sound from fans. In many homes and offices, the noise from a ceiling fan can be distracting. Using Acoustics CFD, we can create a computer simulation to predict this noise. This report details a Ceiling Fan Noise Fluent simulation, which uses the powerful ANSYS Fluent software. A special method called the FW-H Acoustic model is used. This FW-H Acoustic CFD technique takes the information about the moving air and calculates the sound it creates. The main goal of an Acoustics Fluent study like this is to predict the sound level and find the main causes of the noise. This helps engineers design quieter, more comfortable fans. For more acoustics simulations, see the acoustics page here.

Figure 1: The room and ceiling fan

 

Simulation Process: Ceiling Fan Noise CFD Modeling using FW-H Acoustic in ANSYS Fluent

To accurately simulate the Ceiling Fan Noise CFD model, a complete 3D geometry of a room with a central ceiling fan was created. This digital model includes the fan’s three blades, the central hub, and the surrounding room walls, which is essential for a realistic acoustic analysis. To simulate the fan’s rotation, the Sliding Mesh technique was used in ANSYS Fluent. This powerful feature creates a moving zone of mesh around the fan that rotates at its real speed of 250 RPM, while the mesh for the room remains stationary.  After setting up the fluid flow, the Ffowcs Williams-Hawkings (FW-H) acoustic model was activated in Fluent. The FW-H Acoustic Fluent model is an advanced tool that acts like a virtual microphone. To capture this sound, two “receivers” were placed in the simulation at 0.5 meters and 1.5 meters below the fan. This setup allows us to not only predict the fan’s noise but also understand how that noise travels and weakens as it moves away from the source.

Figure 2:  Close-up of the fan geometry and the placement of the five acoustic receivers.

 

Post-processing: Studying Aerodynamic Noise with the FW-H Model

After completing the transient solution of the sliding mesh simulation, the Ffowcs Williams–Hawkings (FW-H) model was applied to extract acoustic data from the unsteady flow field. The rotor wall was set as the acoustic source zone (Figure below), ensuring that the wall pressure fluctuations were fully captured as the primary input for noise prediction. A total of five fixed receivers were strategically positioned beneath the ceiling fan, as shown in Table 1, to evaluate how the tonal and broadband noise levels attenuate with distance and direction.

Table 1 – Receiver coordinates used in this study

Receiver 1 – Close Proximity

At 0.5 m directly below the fan, Receiver 1 records the highest sound pressure levels (SPL) due to minimal geometric spreading loss. The dominant frequency component corresponds to the blade-passing frequency (BPF), with secondary peaks at its harmonics. The high-energy tonal peaks indicate that near-field flow–blade interactions are the primary noise drivers.

Figure 3: Instantaneous sound pressure variation measured 0.5 m below the fan, showing high-amplitude oscillations dominated by the blade-passing frequency.

Figure 4: FFT analysis highlighting a strong tonal peak at the BPF and its harmonics, with elevated broadband noise due to near-field turbulent interactions.

Receiver 2 – Intermediate Distance

Located 1 m below the fan, Receiver 2 exhibits a noticeable SPL drop, primarily due to spherical spreading and partial destructive interference. While the BPF is still evident, its magnitude is lower, and the broadband noise floor is slightly reduced.

Figure 5: Reduced amplitude oscillations compared to Receiver 1, due to greater distance and partial destructive interference.

Figure 6: Clear BPF peak with diminished magnitude, and a slightly lower broadband noise floor.

Receiver 3 – Elevated Offset

Receiver 3 is offset upward (Z = 1.5 m) and captures a distinct spectral profile. The direct line-of-sight to the blade tips amplifies certain high-frequency components, highlighting the sensitivity of fan acoustics to vertical positioning relative to the rotor plane.

Figure 7: Elevated offset measurement showing moderate amplitude oscillations with distinct high-frequency fluctuations.

Figure 8: Enhanced high-frequency content caused by direct exposure to blade tip vortices and wake structures

Receiver 4 – Lateral Position

At 1.5 m lateral offset, Receiver 4 captures more diffused sound energy. The spectrum shows a reduced dominance of tonal peaks, replaced by an increase in mid-frequency broadband noise—likely scattered by the room walls and ceiling.

Figure 9: Lateral position recording showing more irregular waveform due to multipath propagation and reflections

Figure 9: Less prominent tonal peak; mid-frequency broadband noise dominates due to scattering by room boundaries

Receiver 5 – Corner Location

Receiver 5, placed in the room corner (1.5 m lateral and elevated), reveals the strongest influence of reflections and diffraction. The SPL curve exhibits multiple interference-induced fluctuations, making it the most complex spectrum among the five receivers.

Figure 10: Complex oscillatory pattern combining direct sound and multiple reflections from the room boundaries.

Figure 11: Multiple interference-induced peaks across the mid- and high-frequency range, creating a non-uniform SPL profile.

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Figure-by-Figure Interpretation:

• Figures for Receivers 1–5 in the results illustrate both time–domain pressure waveforms and frequency–domain spectra. Each plot clearly shows the relationship between distance, angle, and SPL magnitude.
• The spectrograms confirm that the blade-passing frequency is the primary tonal component, while room boundaries shape the mid–high frequency range.

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The FW-H post-processing successfully identified the spatial variation of aerodynamic noise generated by the ceiling fan. Noise levels are highest directly beneath the fan and attenuate with distance due to spreading, absorption, and interference. The analysis confirms that careful blade design, combined with optimized room acoustics, can substantially reduce perceived noise levels for occupants.