• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.78-83
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• 2003

General algorithm is developed for the prediction of internal flow-induced noise. This algorithm is based on the integral formula derived by using the General Green Function, Lighthills acoustic analogy and Curls extension of Lighthills. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve are compared with actual measurements. This illustrative computation shows that the current method permits generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.4
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• pp.310-318
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• 2004

For many industrial problems originating from aerodynamic noise, noise prediction techniques, reliable and easy to apply, would be of great value to engineers and manufacturers. General algorithm is presented for the prediction of internal flow-induced noise from quick opening throttle valve in an automotive engine. This algorithm is based on the integral formula derived by using the General Green Function, Lighthill's acoustic analogy and Curle's extension of Lighthill's. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve show good agreement with actual measurements. The results show that the dipole noise is dominant in this phenomena and the origin of noise sources is attributed to the anti-vortex lines formed in the down-stream from a throttle valve. This illustrative computation shows that the current method permits generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4E
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• pp.183-196
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• 2003

General algorithm is developed for the prediction of internal flow-induced noise. This algorithm is based on the integral formula derived by using the General Green Function, Lighthill's acoustic analogy and Curl's extension of Lighthill's. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve are compared with actual measurements. This illustrative computation shows that the current method penn its generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1318-1320
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• 2007

Fan noise prediction method is presented for air conditioning and/or cooling system applications where fan acts as an internal equipment having very complicated flow interaction with other various system components. The internal flow paths and distribution in the fan-applied systems such as computer or air conditioner are analyzed by using the FNM(Flow Network Modeling) with the flow resistances for flow elements of the system. Based on the fan operation point predicted from the FNM analysis results, the present fan noise model predicts overall sound power, pressure levels and spectrum. The predictions of the flow distribution, the fan operation and the noise level in electronic system by the present method are well agreed with 3-D CFD and actual noise test results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.9
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• pp.952-960
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• 2008

Fan noise prediction method is presented for air conditioning, automobile and electronic cooling system applications where fan acts as an internal equipment having very complicated flow interaction with other various system components. The internal flow paths and distribution in the fan-applied systems such as computer or air conditioner are analyzed by using the FNM(flow network modeling). Fan noise prediction method comprises two models for the discrete frequency noise due to rotating steady aerodynamic lift and blade interaction and for the broadband noise due to turbulent boundary layer and wake vortex shedding. Based on the fan operation point predicted from the FNM analysis results and fan design parameters, the present far noise model predicts overall sound pressure level and spectrum. The predictions for the flow distribution, the fan operation and the noise level in air cooling system by the present method are well agreed with 3-D CFD and actual noise test results.

• The KSFM Journal of Fluid Machinery
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• v.13 no.2
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• pp.48-53
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• 2010

A computerized design system of axial fan is developed for constructing 3-D blade geometry and predicting both aerodynamic performance and noise. The aerodynamic blading design of fan is conducted by blade angle distribution, camber line determination, airfoil thickness distribution and blade element stacking along spanwise distance. The internal flow and the aerodynamic performance of designed fan are predicted by the through-flow modeling technique with flow deviation and pressure loss correlations. Based on the predicted internal flow field and performance data, fan noise is predicted by two models for discrete frequency and broadband noise sources. The present predictions of the flow distribution, the performance and the noise level of actual fans are well agreed with measurement results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.12
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• pp.1138-1145
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• 2011

The internal broadband noise of a centrifugal fan in a household refrigerator is predicted using hybrid CAA techniques based on stochastic turbulent synthetic model. First, the unsteady flow field around the centrifugal fan is predicted using computational fluid dynamics(CFD) method. Then, the turbulent flow field is synthesized by applying the stochastic turbulent synthetic technique to the predicted flow field. The aerodynamic noise sources of the centrifugal fan are modeled on a basis of the synthesized turbulent field. Finally, the internal broadband noise of the centrifugal fan is predicted using the boundary element method(BEM) and the modeled sources. The predicted noise spectrum is compared with the experimental data. It is found that the predicted result closely follows the experimental data. The proposed method can be used as an effective tool for designing low-noise fans without expensive computational cost required generally for the LES and DNS simulations to resolve the turbulence flow field responsible for the broadband noise.

• Journal of the Korean Society of Visualization
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• v.22 no.2
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• pp.55-62
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• 2024

Using an internal flow noise test bench, this study investigates the variation in internal flow noise at the inlet and outlet monitoring points of a DN100 T-junction pipe under different flow velocities. Results indicate that with increasing flow velocity, both the sound pressure level and total sound pressure level at the inlet and outlet monitoring points increase. The highest total sound pressure level is observed at the vertical outlet monitoring point B, followed by the horizontal inlet monitoring point A, with the lowest at the horizontal outlet monitoring point C. At a constant flow velocity, the sound pressure level at the inlet and outlet points initially increases and then decreases as frequency increases.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.10
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• pp.763-769
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• 2014

This study is on the experiment and prediction of the pipe noise due to the internal fluid. The vibration of pipe external surface and noise in air were measured according to the internal fluid velocity and pipe type. In the experiment, the vibration and noise level of the straight pipe and rounded pipes show that the vibration and noise level are almost same. The 900 mitred pipe shows the high vibration and noise level. In the prediction of noise due to the internal flow, the method using the pipe surface vibration and radiation efficiency shows good agreement with experimental result.

• International Journal of Fluid Machinery and Systems
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• v.2 no.1
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• pp.80-91
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• 2009

In this study, a prediction theory for specific noise that is the overall characteristic of the fan has been proposed. This theory is based on total pressure prediction and broadband noise prediction. The specific noises of two forward curved fans with different number of blades were predicted. The flow around the impeller having 120 blades (MF120) was more biased at a certain positions than the impeller with 40 blades (MF40). An effective domain of the energy conversion of MF40 has extended overall than MF120. The total pressure was affected by the slip factor and pressure loss caused by the vortex flow. The suppression of a major pressure drop by the vortex flow and expansion of the effective domain for energy conversion contributed to an increase in the total pressure of MF40 at the design point. The position of maximum relative velocity was different for each fan. The relative velocity of MF120 was less than that of MF40 due to the deviation angle. The specific noise of MF120 was 2.7 dB less than that of MF40 due to the difference in internal flow. It has been quantitatively estimated that the deceleration in the relative velocity contributed to the improvement in the overall performance.