• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.110-116
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• 2000

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.

• 소음진동
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• 제10권5호
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• pp.792-799
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• 2000

Aircraft noise in the vicinity of Kimpo international airport has damaged to large number of people who live in communities. This paper investigates noise exposed area due to aircraft flight based on prediction modeling program INM and flight path data. Especially effect on route for aircraft has been considered. Ti also examines noise impact for various flight modes, such as a thrust cutback climb method.

• 한국소음진동공학회논문집
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• 제20권6호
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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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.78-83
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• 2000

Exterior noise generated by the aircraft induces a serious noise pollution near the airport. For the prediction of an exterior noise radiation of aircraft an empirical formula is employed to model the acoustic sources. It is shown that the fan/compressor noise is the most dominant part of the acoustic sources in all cases.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 춘계학술대회논문집
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• pp.849-854
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• 2000

Statistical energy analysis is suitable for shipboard noise prediction in many respects. It could effectively model the large and complicated ship structures for noise analysis. This paper introduces the procedure of SEA for shipboard noise analysis gained from author's experiences in the past few years. Also, prediction accuracies of shipboard noise analysis using statistical energy analysis are discussed. It is found that the prediction results could be much improved when using the actual measured data of source levels and material properties such as loss factors, absorption coefficients and etc.

• 한국소음진동공학회논문집
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• 제18권9호
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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.

• 반도체디스플레이기술학회지
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• 제19권4호
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• pp.88-93
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• 2020

Based on the capture-emission energy (CEE) maps of CMOS devices, a physics-informed machine learning model for the bias temperature instability (BTI)-induced threshold voltage shifts and low frequency noise is presented. In order to incorporate physics theories into the machine learning model, the integration of artificial neural network (IANN) is employed for the computation of the threshold voltage shifts and low frequency noise. The model combines the computational efficiency of IANN with the optimal estimation of Gaussian mixture model (GMM) with soft clustering. It enables full lifetime prediction of BTI under various stress and recovery conditions and provides accurate prediction of the dynamic behavior of the original measured data.

• International Journal of Railway
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• 제4권2호
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• pp.42-49
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• 2011

Today, rolling stock has become a fast and convenient mode of transportation and has witnessed increased demand. But the speed improvement has resulted in increased aerodynamic noise and therefore residential districts near the railroad tracks are exposed to ever increasing noise level. A study on methodologies for measuring and appraising rolling stock's environmental noise has therefore become an important area of endeavor. In the case of the environmental noise, there are no changes in tone so prediction can be made by reducing areas around the railway. The present study explores estimation of the noise around the railway using scale model, and the source of the noise has been investigated as well. The scale model of rolling stock will have to be able to measure high frequency noise and it is required to be generated in a short amount of time. Since popping a balloon or firing a gun fits this requirement the present study analyzed the characteristics of these two different noise sources. Measurement was made in a large vacant lot and the reflection due to the ground was also examined. The method proposed here can be used in the future for predicting the environmental noise of railway vehicles.

• 한국음향학회지
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• 제21권2호
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• pp.134-141
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• 2002

본 연구에서 곡선 와동 요소와 CVC (Constant Vorticity Contour) 후류 모델이 수평축 풍력 터빈의 공력 성능 및 소음을 예측하기 위해 사용되었다. 또한 2차 회귀에 근거하여 회전수의 예측을 하였다. 광대역 소음을 예측은 경험식에 근거한 방법을 사용하였다. 직선 와동요소 대신에 BCVE (Basic Curved Vortex Element)와 SIVE(Self Induction Vortex Element)를 사용하는 곡선 와동 요소를 사용하였으며 CVC 후류 모델에서 와동의 강도는 블레이드의 스팬방향 및 와동을 따라서 일정하다고 가정하였다. 이렇게 만들어진 자유 후류는 와동 격자를 대치한다. 본 방법은 여타의 방법에 비해 휠씬 적은 계산 시간을 요구하며 후류의 정확한 구조를 모사할 수 있었다. 검증을 위해서는 김준모의 실험과 Zond사의 Z-40FS의 모델을 성능 예측 결과와 WTS-4와 USWP를 소음 예측 결과와 비교하였다. 계산 결과는 실제의 실험치와 잘 일치하는 것으로 나타났다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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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.