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Unsteady Fast Random Particle Mesh method for efficient prediction of tonal and broadband noises of a centrifugal fan unit
Author(s) -
Seongmin Heo,
Cheolung Cheong,
Tae-Hoon Kim
Publication year - 2015
Publication title -
aip advances
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 58
ISSN - 2158-3226
DOI - 10.1063/1.4930979
Subject(s) - reynolds averaged navier–stokes equations , acoustics , centrifugal fan , computational fluid dynamics , turbulence , sound pressure , noise (video) , engineering , physics , computer science , mechanics , mechanical engineering , artificial intelligence , image (mathematics) , inlet
In this study, efficient numerical method is proposed for predicting tonal and broadband noises of a centrifugal fan unit. The proposed method is based on Hybrid Computational Aero-Acoustic (H-CAA) techniques combined with Unsteady Fast Random Particle Mesh (U-FRPM) method. The U-FRPM method is developed by extending the FRPM method proposed by Ewert et al. and is utilized to synthesize turbulence flow field from unsteady RANS solutions. The H-CAA technique combined with U-FRPM method is applied to predict broadband as well as tonal noises of a centrifugal fan unit in a household refrigerator. Firstly, unsteady flow field driven by a rotating fan is computed by solving the RANS equations with Computational Fluid Dynamic (CFD) techniques. Main source regions around the rotating fan are identified by examining the computed flow fields. Then, turbulence flow fields in the main source regions are synthesized by applying the U-FRPM method. The acoustic analogy is applied to model acoustic sources in the main source regions. Finally, the centrifugal fan noise is predicted by feeding the modeled acoustic sources into an acoustic solver based on the Boundary Element Method (BEM). The sound spectral levels predicted using the current numerical method show good agreements with the measured spectra at the Blade Pass Frequencies (BPFs) as well as in the high frequency range. On the more, the present method enables quantitative assessment of relative contributions of identified source regions to the sound field by comparing predicted sound pressure spectrum due to modeled sources

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