Towards Quieter Air-Cooling Systems: Rotor Self-Noise Prediction for Axial Cooling Fans - Persoons, Tim; Wasala, Sahan; Zhao, Wenguang (My University, 2022)
Aeroacoustic noise is seen as a major threat to the survival of air cooling for electronics systems. The application of numerical noise prediction methods is highly constrained by computational costs. A reduced-order model (ROM) was proposed in this study to predict the rotor self-noise for axial cooling fans based on the blade element theory (BET), lifting line theory and Amiet's trailing-edge noise model. The accuracy of this ROM was validated against available benchmark case and experimental data. The ROM is able to accurately predict the fan characteristic and the broadband noise in the high frequency range (above 2 kHz), while the computational speed is more than 3 orders of magnitude than a high-fidelity simulation method, making it appropriate for low-noise fan design and optimization.
2022 28th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)
PUBLISHED
Dublin, Ireland
Keywords: electronics cooling; aeroacoustics; reduced-order modeling; fan curve; blade element theory; Amiet's model; Smart & Sustainable Planet; Telecommunications