• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.709-714
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• 2008

The various computer programs are used in computer simulation of the traffic noise prediction. But the difference or problem of calculation method used for road traffic noise prediction is not exactly investigated. In this paper, Road traffic noise is predicted on the specific regions by using four prediction methods such as XPS31-133 model(France), RLS-90 model(Germany), ASJ RTN model(Japan) and FHWA model(U.S.A.), which are operated by a program named SoundPLAN, a program to predict road traffic noise. Those prediction values are compared with a measurement value. The results show that four prediction values for taraffic noise are a little different, because of various input factors according to the prediction methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.882-888
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• 2008

The increase in logistics and the emergence of high speed vehicles are aggravating the noise problem, and disturbing large numbers of people. Therefore, growing attention is being paid to the creation and utilization of a noise map in order to grasp and predict the influence of noise, and to establish a policy that effectively reduces noise. However, so far there has been little progress in developing a predictive formula for railway noise, and a noise prediction program suitable for the domestic environment. Therefore, there is a need for a method to apply the overseas prediction formula to domestic railway vehicles. This study evaluated the prediction method, the result of which is similar to that of a real measurement, using a noise map. It also employed a commercial software program, SoundPlan, to predict noise.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.942-946
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• 2010

As the major sources of interior noise of train at running condition are the wheel/rail contact noise, the traction motor's noise and the driving gear's noise and these noise sources are transmitted through the car body, the noises of HVAC and air duct can be ignored. But the interior noise of train at standstill condition is decided by HVAC's noise and noise from the diffuser through the air duct. the interior noise prediction of train at standstill condition should be performed considering the shape of air duct, the air velocity and noise reduction property inside the air duct. But it is hard to estimate the interior noise level by the numerical method. Therefore train maker predict the interior noise level using The commercial noise prediction program. This paper introduce the noise prediction method of the train at standstill condition using the commercial program appling the ray tracing method and statistical energy analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.872-876
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• 2007

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.2
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• pp.193-197
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• 2012

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• New & Renewable Energy
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• v.16 no.2
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• pp.1-13
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• 2020

The reduction of noise from wind turbines has been studied using various methods. Some examples include controlling wind turbine blades, designing low-noise-emitting wind turbine blades, and using trailing-edge serrations. Among these methods, serration is considered an effective noise reduction method. Various studies have aimed to understand the effects of trailing-edge serration parameters. Most studies, however, have focused on fixed-wing concepts, and few have analyzed noise reduction or developed a prediction method for rotor-type blades. Herein, a noise prediction method, composed of two noise prediction methods for a wind turbine with trailing-edge serrations, is proposed. From the flow information obtained by an in-house program (WINFAS), the noise from non-serrated blades is calculated by turbulent ingestion noise and airfoil self-noise prediction methods. The degree of noise reduction caused by the trailing-edge serrations is predicted in the frequency domain by Lyu's method. The amount of noise reduction is subtracted from the predicted result of the non-serrated blade and the total reduction of the noise from the rotor blades is calculated.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.6
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• pp.555-561
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• 2010

Predicted noise level has been used to assess the annoyance response since noise map was generalized and being the normal method to assess the environmental noise. Unfortunately using predicted noise level to derive the annoyance prediction curve caused some problems. The data have to be grouped manually to use the annoyance prediction curve. The aim of this paper is to propose the method to handle the predicted noise level and the survey data for annoyance prediction curve. This paper used the percentage of persons annoyed(%A) and the percentage of persons highly annoyed as the descriptor of noise annoyance in a population. The logistic regression method was used for deriving annoyance prediction curve. It is concluded that the method of dichotomizing data and logistic regression was suitable to handle the predicted noise level and survey data.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.25-29
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• 2006

Noise map presents new alternatives of noise reduction counter measure and becomes important tool for making environmental policy. Many input factors such as road conditions, number of vehicles, speeds of vehicles are used for noise prediction of the noise map. However, results of noise prediction make difference depending on the values of the input factors. In this study, effect of measurement method for vehicle speeds all the prediction results of the noise map.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.2 s.119
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• pp.155-159
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• 2007

Noise map presents new alternatives of noise reduction counter measure and becomes important tool for making environmental policy. Many input factors such as road conditions, number of vehicles, speeds of vehicles are used for noise prediction of the noise map. However, results of noise prediction make difference depending on the values of the input factors. In this study, it researched effect of measurement method for vehicle speeds on the prediction results of the noise map.

• 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.