• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.939-942
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• 2014

고속도로 교통 소음 저감을 위해 상용소음예측프로그램인 SoundPLAN과 소음예측 시 주로 사용하는 도로 교통 소음예측식인 RLS-90을 이용하여 경제적이고 효율적인 방음대책 설계방안에 대한 연구를 하였다. 대상지역에서 측정한 실제 소음도와 예측 소음도의 차이를 비교하여 모델을 검증하고 장래교통량에 대하여 소음을 예측하여 방음대책을 설계하였다. 방음벽의 높이와 길이, 저소음 포장의 길이를 조절하고 저소음 포장과 방음벽을 혼용했을 경우에 대하여 소음규제 기준에 적합하게 설계하였고 각각의 설치 단가를 이용하여 경제성을 비교하여 보다 효율적인 방음대책을 알아보았다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.153-158
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• 2012

Noise maps are produced according to 'The Method of making a Noise Map' in order to noise control efficiently, and prediction model to predict road traffic noise which may apply to Korean situation, include CRTN, RLS 90, NMPB, Nord 2000 and ASJ 2003. Of them, ASJ 2003, Japan's prediction model has not been verified for the application to Korean situation according to the classification of vehicle. In addition, ASJ 2003 was revised to ASJ 2008 recently, a classification for motorcycle was added. This study attempts to check the classification of vehicle in ASJ 2008 and 'The Method of making a Noise Map' to confirm the suitability of the application of them to Korean situation.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.161-166
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• 2012

This Study, as part of a study on the application plan of overseas noise prediction models suitable for making domestic noise maps, analyzed the correlation between the differences in predicted noise levels by individual noise prediction model and surveyed data on General roads and Expressways. Separation distances of 5m and 10m, respectively were set from the ends of the general roads and the expressways at the points of measurements and to check the distribution patterns of sound power levels, the levels were measured at the heights of 1.5m and 3m, respectively. The latest revised versions of the five models (CRTN, RLS90, NMPB, Nord2000, ASJ2008) suggested in The Method of making Noise Maps were used as prediction models, and predicted noise levels were calculated by using commercial software SoundPLAN (Ver 7.1).

• 환경영향평가
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• 제21권4호
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• pp.567-572
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• 2012

This paper suggests the set-up plan of the assessment scope in road noise considering road characteristics with the prediction model of road noise. The RLS90 prediction model with some assumptions is used to establish the assessment scope of road noise. The main contents of the applied assumptions are smooth drive of cars, flat region, location of all noise sources in one lane, drive in design speed, and set-up of assessment scope according to traffic volume and car speed. The information of traffic volume to predict road noise is obtained by the distribution of small cars and full-sized cars in road. In this study, the total traffic volume in road is computed by adding the number of small cars to the conversion number of small cars, which means the number of small cars making the same noise as one full-sized car. The prediction result of road noise with the influence factor of traffic volume, car speed, distance between road and receiver is presented. The resultant assessment scope of road noise is obtained by combining road noise prediction data with the set-up standard of road noise assessment scope.

• 한국환경과학회지
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• 제16권7호
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• pp.823-830
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• 2007

Traffic noise is a kind of noise caused by cars, trains and aircraft. Among them, noise produced by cars is the most important factor in cities. According to the National Institute of Environmental Research(NIER)'s survey, Road traffic noise levels in Susan are the highest of all the cities in Korea. So, appropriate measures for road traffic noise reduction is required. For this purpose, the construction of a noise map in Susan will playa vital role. However, road traffic noise formulas are constructed considering regional characteristics such as each country road's environment and vehicle quality. Therefore, prior to constructing a noise map in Susan, examination processes about each formula constituent status and estimation process are required preferentially. In this research, the basic first stage is to estimate Susan's road traffic noise. First, investigate characteristics of each road traffic noise estimate and using this, a noise map is constructed for road traffic noise in Susan. Then the adaptation of a road traffic noise formula is evaluated.