Reduction of motor fan noise using CFD and CAA simulations

Krishna, S.; Krishna, A. Rama; Ramji, K.

doi:10.1016/j.apacoust.2011.06.008

Cited by 35 publications

(24 citation statements)

References 19 publications

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“…Firstly, the pressure field of three kinds of fans is solved by LES model. After the pressure field stabilized, the acoustics model is used for noise analysis [17,18]. The central section of each fan when the pressure field is stable is shown in Figs.…”

Section: Simulation Of Aerodynamic Noisesmentioning

confidence: 99%

Acoustic characteristic analysis of the non-smooth surface fan of off-highway machinery

Yang¹,

Qin²,

Liu³

2017

J. vibroeng.

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Cooling fan, as an important component of the Off-Highway machinery cooling system, is becoming the largest noise source when it is rotating fast. So, it is the key to suppress the noise from cooling fan in reducing noise in the Off-Highway machinery. In this study, we designed a kind of non-smooth surface cooling fan which could reduce noise strongly, by adding two kinds of non-smooth features on the smooth surface of the forward-skewed fan, and also combining the CFD virtual wind tunnel simulation with bench test to analyze features of flow field and noise. Comparing the experimental data shows that the new fan effectively suppressed the vortex of the power cabin; the effect to reduce noise is proportional to the rotate speed, and with the rated speed, the total noise is reduced 20.9 % and the peak noise is reduced 21.5 % than the original arc bending plate fan in wheel loaders.

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Section: Simulation Of Aerodynamic Noisesmentioning

confidence: 99%

Acoustic characteristic analysis of the non-smooth surface fan of off-highway machinery

Yang¹,

Qin²,

Liu³

2017

J. vibroeng.

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“…In the first studies, experimental approach is used to estimate the propagation of sound waves. But nowadays, along with the increasing the computational power of computers, numerical simulations of noise generated by fluid flow, called Computational Aero-Acoustic (CAA), has been widely used by researchers [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Synergy between Noise Reduction Techniques Applied in Different Industries: A Review

2020

IJM

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This review aims to assist aerodynamic noise in three industrial fields: Aerospace, Turbomachinery and Automotive. In this review the general terms in aeroacoustics is defined; and aerodynamic noise sources are recognized. The paper also reviews the brief literature on noise reduction techniques, with a particular focus on the state of the art numerical and experimental works. In Addition, developments in low speed designs for aerodynamic noise reduction, some passive and active methods for example serrated boundaries, porous media, noise absorber, and etc. are discussed. By investigating similarities in noise reduction techniques between these industries, this paper offers an outlook for noise reduction techniques in future.

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“…Predicting the noise generated aerodynamically is relatively straightforward once detailed aerodynamics involved in the propulsion system is available through the use of direct noise computation or hybrid prediction. Aeroacoustic investigations [1][2][3] or optimizations in that framework are possible 4,5 but demanding in terms of computational cost, hence not realistic in an industrial context. To this aim, lower-fidelity tools are needed.…”

Section: Introductionmentioning

confidence: 99%

Towards silent micro-air vehicles: optimization of a low Reynolds number rotor in hover

Serré

Gourdain

Jardin

et al. 2019

International Journal of Aeroacoustics

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The demand in micro-air vehicles is increasing as well as their potential missions. Either for discretion in military operations or noise pollution in civilian use, noise reduction of micro-air vehicles is a goal to achieve. Aeroacoustic research has long been focusing on full scale rotorcrafts. At micro-air vehicle scales however, the hierarchization of the numerous sources of noise is not straightforward, as a consequence of the relatively low Reynolds number that ranges typically from 5000 to 100,000 and low Mach number of approximately 0.1. This knowledge, however, is crucial for aeroacoustic optimization and blade noise reduction in drones. This contribution briefly describes a low-cost, numerical methodology to achieve noise reduction by optimization of micro-air vehicle rotor blade geometry. Acoustic power measurements show a reduction of 8 dB(A). The innovative rotor blade geometry allowing this noise reduction is then analysed in detail, both experimentally and numerically with large eddy simulation using lattice Boltzmann method. Turbulence interaction noise is shown to be a major source of noise in this configuration of low Reynolds number rotor in hover, as a result of small scale turbulence and high frequency unsteady aeroadynamics impinging the blades at the leading edge.

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Reduction of motor fan noise using CFD and CAA simulations

Cited by 35 publications

References 19 publications

Acoustic characteristic analysis of the non-smooth surface fan of off-highway machinery

Acoustic characteristic analysis of the non-smooth surface fan of off-highway machinery

Synergy between Noise Reduction Techniques Applied in Different Industries: A Review

Towards silent micro-air vehicles: optimization of a low Reynolds number rotor in hover

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