• Journal of Environmental Impact Assessment
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• 제15권2호
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• pp.93-100
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• 2006

In general, the verification to prediction formula in a national road and the main street of a town has been used recklessly in Korea. Therefore we investigated the validity of an existing prediction formula (NIER(87, 99), TR-Noise, KLC(2002)) with correction relationship which was based on both the prediction formular from apartment complex in the field and height 1.5m from the surface level. On the results of measuring the noise level form an isolated distance, the noise level showed that it was 4.5~5.5dB(A) by reason of becoming 2 folder far from a source. From the distribution of noise level measured by the apartment floors, the measurement point (1st floor) was 58.7~71.4dB(A) at its lowest level and the middle floors (3, 5, 7 and 10) were the highest distribution of noise level. From the analysis results on the application validity to an existing prediction formular (NIER(87, 99), TR-Noise, KLC(2002)) in the height 1.5m, the correction coefficients were 0.95~0.96 and the measured values were reasonably close to the predicted values, indicating the validity and adequacy of the predicted models. KLC(2002) model was found accurate within 3dB(A) with 36 data out of the total 42 data, showing the most accuracy among the predict models. However, the developed models have to improve the accuracy with a various of factors.

• Proceedings of the KSR Conference
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.545-550
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• 2007

The objective of this paper is to suggest a characteristics of Noise and the Noise Prediction Model and the appropriate Noise Impact Mitigation Method for a elevated railway bridges construction. The characteristics on noises are investigated and evaluated according to a type of railway bridges such as steel, concrete and steel/concrete compound bridges, a types of train, a distance and height from railways. The noise prediction study has been made by the evaluation of differences between model values and in-situ measurement, around the railways. For the noise prediction, the Mithra program and the electronic properties of noises have been adopted.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• 제26권1호
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• pp.49-54
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• 2016

The wind power plants were installed in many places because of the low climate changing effects since 2000. Generally, the wind power plants located in the seaside and the mountainous area and the heights of the windmills are about 40 m~140 m above the ground level. So the noises emitted from the wind power plants propagate far away compared with other environment noise sources like trains and cars noise. Because of these reasons, the noise emitted from the wind power plant is easy to cause the additional social problems like as noise complaints. Under the situation, the ministry of environment has established the guideline to evaluate the environmental effects for the wind power plant. According to the guideline, the noise of the wind power plant has to meet 55 dB(A) at daytime and 45 dB(A) at night in the residential area, which is regulated in the noise and vibration management law. But, it is difficult to estimate the noise emitted from the wind power plant because of the absence of the prediction model of the wind power plant noise. Therefore, the noise prediction model for wind power plants using the regression analysis method is developed in this study. For the development of the model, the sound pressure levels of the wind power plants in Jeju island are measured and the correlations between the sound pressure levels are analyzed. Finally, the prediction equation of the wind power plant noise using by regression analysis method derived. The prediction equation for the wind power plant noise proposed in this study can be useful to evaluate the environmental effects in any wind power plant development district.

• Proceedings of the KSR Conference
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.2852-2859
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• 2011

Planning and construction of railway for high speed trains up to 400 km/h are recently driven in Korea. High speed train is one of the environment-friendly fastest mass transportation means but its noise generated by rolling, traction and aerodynamic mechanism can cause public complaints of residents nearby railways. To cost-effectively prevent the troublesome noise in a railway planning stage, the rational railway noise prediction method considering the characteristics of trains as well as railway structures should be required but it is difficult to find an authentic method for Korean high speed trains such as KTX and KTX-II. In this study, recent railway noise prediction methods developed by EU countries are introduced and discussed for consulting before setting the framework of our own railway noise prediction model emitted by Korean high speed trains over 250 km/h. Especially, the new Schall 03 model (2006) developed by Germany and IMAGINE model (2007) suggested by an EU framework research project are intensively reviewed. In addition, research items required for the development of our own model are suggested.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• 제14권8호
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• pp.777-786
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• 2003

The phase noise characteristics of the phase-locked loop frequency synthesizer were predicted based on the analysis for phase noise contribution of noise sources. The proposed phase noise model in this paper more accurately predicts the phase noise spectrum of frequency synthesizer. To accurately model the phase noise contribution of noise sources in frequency synthesizer, the phase noise sources were analyzed via modeling of the frequency divider and phase noise components using Leeson model for reference signal source and VCO. The phase noise transfer functions to VCO from noise sources were analyzed by superposition theory and linear operation of phase-locked loop. To evaluate the phase noise prediction model, the frequency synthesizers were fabricated and were evaluated by measured data and prediction data.

• Journal of Environmental Impact Assessment
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• 제26권1호
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• pp.11-26
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• 2017

Approximate empirical equations obtained by measuring overall noise levels at different distances have been used to evaluate environmental influence of the railway noise though the accurate prediction of noise levels is important. In this paper, a noise prediction model considering the frequency characteristics of noise sources and propagation was suggested to improve the accuracy of noise prediction. The railway noise source was assorted into track, wheel, traction and aerodynamic components and they were characterized with the source strength and speed coefficient at each octave-band frequency. Correction terms for the acoustic roughness and the track/bridge condition were introduced. The sound attenuation from a source to a receiver was calculated taking account of the geometrical divergence, atmospheric absorption, ground effect, diffraction at obstacles and directivity of source by applying ISO 9613-2. For obtaining the source strength and speed coefficients, the results of rolling noise model, numerical analysis and measurements of pass-by noise were analyzed. We compared the predicted and measured noise levels in various vehicles and tracks, and verified the accuracy of the present model. It is found that the present model gives less error than the conventional one, so that it can be applied to make the accurate prediction of railway noise effect and establish its countermeasures efficiently.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2006년도 추계학술대회논문집
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• pp.30-33
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• 2006

The purpose of this study is the improvement of the prediction model of highway noise. It includes the measurement and analysis of the highway noise for various types of roads and environments. The results of the measurement are compared with the noise levels predicted by highway noise prediction models including domestic and foreign ones and any recommendation to improve the accuracy of the models should be provided.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.505-509
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• 2008

This paper studied the efficient noise prediction method for new apartment house near the road traffic noise. Three noise prediction software were compared by each prediction noise level using the simple model which is included the road, soundproofing wall and building. Two foreign national calculation models(RLS-90 and NMPB) were verified by comparison of measured sound level. Frequency of sound level was predicted by NMPB and compared by measured data. The sphere of noise source and facade reflection were proposed to accurate predict the road traffic noise in new apartment house.

• Proceedings of the KSR Conference
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• 한국철도학회 2003년도 추계학술대회 논문집(III)
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• pp.132-137
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• 2003

This paper concerns the prediction of railway noise propagation using scale model experiment in acoustics. In order to make acoustical experiment the digital signal processing technique are applied and spark discharge sound sources have been developed in which impulse response measured in 1/20 scale model railway. In the case of scale model experiment, it is difficult to realize sufficiently small size and directivity and to get sufficient sound energy and to get repeatability. Several type of Spark discharge sound source is made in laboratory. Experiment results are compared with the calculated results by the prediction model. As the results, it was found that railway noise could be predicted in acoustical scale model experiment using spark discharge sound source.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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• pp.728-734
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• 1998

Aircraft noise is one of the main causes of environmental impact. It is more serious than any other noise nuisance. It has become an increasing source of annoyance to the large number of people who live in communities near airports. This paper demonstrates the prediction of aircraft noise using Integrated Noise Model(INM) 5.1 developed by U.S. FAA and aircraft noise contour map near airports.