Numerical simulation on near-field aerodynamic noise of an adjustable-blade axial-flow fan
Source abstract
Abstract
A numerical simulation method based on the Ffowcs-Williams and Hawkings model is employed to predict the mechanisms of the near-field aerodynamic noise distribution characteristics of an adjustable-blade axial-flow fan with different installation angles of moving blades (Δβ). The simulated results reveal that with Δβ changing from −12° to 12°, the changing curves of the maximum total sound pressure level (MTSPL) at the tip clearance region (A region), the leading edge region (B region), and the trailing edge region (C region) exhibit an apparently rising trend, which increase by 4.0 dB, 5.7 dB, and 4.3 dB, respectively. Besides, the MTSPL at the C region is always smaller than that at A and B regions within the studied installation angles. Additionally, the acoustic energy ratio (Cpi) is the ratio of the sound energy density of a certain frequency to the total sound energy density, which shows the various frequency distribution characteristics under studied angles. It is found that when Δβ deflects from −12° to 0°, Cp1 (the acoustic energy ratio at the low-frequency in the range of 20–500) decreases from 0.71 to 0.59, Cp2 (the acoustic energy ratio at the intermediate-frequency in the range of 500–2000) increases from 0.18 to 0.25, and Cp3 (the acoustic energy ratio at the high-frequency in the range of 2000–3000) rises from 0.1 to 0.16. This study derives the aerodynamic distribution characteristics of the TSPL and acoustic energy in the near field of moving blades, which reveals its changing rules and frequency distribution under various installation angles. The conclusions may provide guidance for the research regarding the technology of the noise control of the adjustable-blade axial-flow fan.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Aerodynamics and Acoustics in Jet Flows · Fluid Dynamics and Turbulent Flows · Heat Transfer Mechanisms
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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