• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 추계학술대회 논문집
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• pp.488-493
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• 2011

Authors previously suggested the design sensitivity analysis based on transmissibility function and identified the sensitivity of measured point over the small modification of system dynamics. On the other hand, the acceleration data will not reveal the strain information at the same location and authors suggested energy isoclines that successfully predict the fatigue damage on the interesting location to overcome the drawback of acceleration over fatigue society. Both of methodologies, sensitivity analysis and fatigue damage prediction, commonly use the response acceleration response as main indicator. In this paper, authors investigate the advanced method of vibration fatigue prediction using design sensitivity analysis to enhance the accuracy of predicted accumulated fatigue. Uni-axial vibration testing is performed with finite element model of a simple notched specimen and the prediction of fatigue damage at notched location is conducted for accelerations at different measurement locations that show different sensitivity contribution, either.

• 한국소음진동공학회논문집
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• 제22권2호
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• pp.123-129
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• 2012

It was previously suggested the design sensitivity analysis based on transmissibility function to identify the most sensitive response location over a small design modification. On the other hand, energy isoclines were used to predict the fatigue damage with acceleration response only. Both of previous studies commonly tackle the engineering problem using the acceleration response alone such that it may be possible to investigate the relationship between sensitivity analysis and accumulated fatigue damage. In this paper, it is suggested the novel method of vibration fatigue prediction using design sensitivity analysis to enhance the accuracy of predicted accumulated fatigue. Uni-axial vibration testing is performed with a simple notched specimen and the prediction of fatigue damage is conducted using accelerations measured at different locations. It can be concluded that the accuracy of predicted fatigue damage is proportional to the sensitivity index of the responsible location.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3612-3624
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• 2021

At present, in the case of pump fast optimization, there is a problem of rapid, accurate and effective prediction of cavitation performance. In "A Cavitation Performance Prediction Method for Pumps PART1-Proposal and Feasibility" [1], a new cavitation performance prediction method is proposed, and the feasibility of this method is demonstrated in combination with experiments of a mixed flow pump. However, whether this method is applicable to vane pumps with different specific speeds and whether the prediction results of this method are accurate is still worthy of further study. Combined with the experimental results, the research evaluates the sensitivity and accuracy at different flow rates. For a certain operating condition, the method has better sensitivity to different flow rates. This is suitable for multi-parameter multi-objective optimization of pump impeller. For the test mixed flow pump, the method is more accurate when the area ratios are 13.718% and 13.826%. The cavitation vortex flow is obtained through high-speed camera, and the correlation between cavitation flow structure and cavitation performance is established to provide more scientific support for cavitation performance prediction. The method is not only suitable for cavitation performance prediction of the mixed flow pump, but also can be expanded to cavitation performance prediction of blade type hydraulic machinery, which will solve the problem of rapid prediction of hydraulic machinery cavitation performance.

• KIEE International Transactions on Power Engineering
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• 제11A권4호
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• pp.15-20
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• 2001

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability discusses a methodology to identify crucial transmission lines for stability prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system, and it shows capabilities of the proposed method.

• 한국도로학회논문집
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• 제4권2호
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• pp.9-18
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• 2002

포장의 공용성에 영향을 미치는 주요파손은 소성변형, 피로균열, 종단평탄성이다. 따라서 이들 세가지 파손량에 영향을 미치는 요인들을 분석하고 예측모델을 개발하는 것이 포장의 공용성 관리면에서 중요하다. 본 논문에서는 미국에서 개발되어 다양한 포장구간에 대한 광범위한 데이터가 축적되어 있는 DataPave 프로그램을 이용하여 세가지 파손량과 각각에 영향을 미치는 인자들을 추출한 후 파손 예측모델을 개발하였다. 개발된 모델의 입력변수들이 각각의 파손량에 미치는 영향을 파악하기 위해 민감도분석을 수행하였다. 소성변형 예측모델의 민감도분석결과 아스팔트함량, 공극율, 노상의 최적함수비가 주요영향인자로 나타났으며, 피로균열예측모델의 경우 아스팔트점도, 아스팔트함량, 공극율 순으로 나타났다. 종단평탄성 예측모델 분석결과 아스팔트점도, 노상골재의 200번체 통과율, 아스팔트함량 순으로 영향을 미치는 것을 알 수 있었다.

• 대기
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• 제30권2호
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• pp.103-113
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• 2020

In this study, we analyzed and developed the monitoring system in order to confirm the effect of observations on forecast sensitivity on ensemble-based data assimilation. For this purpose, we developed the Ensemble Forecast Sensitivity to observation (EFSO) monitoring system based on Local Ensemble Transform Kalman Filter (LETKF) system coupled with Korean Integrated Model (KIM). We calculated 24 h error variance of each of observations and then classified as beneficial or detrimental effects. In details, the relative rankings were according to their magnitude and analyzed the forecast sensitivity by region for north, south hemisphere and tropics. We performed cycle experiment in order to confirm the EFSO result whether reliable or not. According to the evaluation of the EFSO monitoring, GPSRO was classified as detrimental observation during the specified period and reanalyzed by data-denial experiment. Data-denial experiment means that we detect detrimental observation using the EFSO and then repeat the analysis and forecast without using the detrimental observations. The accuracy of forecast in the denial of detrimental GPSRO observation is better than that in the default experiment using all of the GPSRO observation. It means that forecast skill score can be improved by not assimilating observation classified as detrimental one by the EFSO monitoring system.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권2호
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• pp.92-102
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• 2017

Purpose: Reliability prediction standards consider environmental conditions, such as temperature, humidity and vibration in order to predict the reliability of the electronics components. There are many types of standards, and each standard has a different failure rate prediction model, and requires different environmental conditions. The purpose of this study is to make a sensitivity analysis by changing the temperature which is one of the environmental conditions. By observing the relation between the temperature and the failure rate, we perform the sensitivity analysis for standards including MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES. Methods: we establish environmental conditions in accordance with maneuver weapon systems's OMS/MP and mission scenarios then predict the reliability using MIL-HDBK-217F, RiAC-HDBK-217Plus and FIDES through the case of DC-DC Converter. Conclusion: Reliability prediction standards show different sensitivities of their failure rates with respect to the changing temperatures.

• 대한전기학회논문지:전력기술부문A
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• 제52권5호
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• pp.271-278
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• 2003

Power system stability is correlated with system structure, disturbances and operating conditions, and power flows on transmission lines are closely related with those conditions. This paper proposes a methodology to identify correlative power flows for power system transient and small-signal stability prediction. In transient stability sense, the Critical Clearing Time is used to select some dominant contingencies, and Transient Stability Prediction index is proposed for the quantitative comparison. For small-signal stability, this paper discusses a methodology to identify crucial transmission lines for stability Prediction by introducing a sensitivity factor based on eigenvalue sensitivity technique. On-line monitoring of the selected lines enables to predict system stability in real-time. Also, a Procedure to make a priority list of monitored transmission lines is proposed. The procedure is applied to a test system and the KEPCO systems in the year of 2003 and it shows capabilities of the proposed method

• 한국대기환경학회지
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• 제18권4호
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• pp.327-334
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• 2002

The work presents sensitivity and uncertainty analysis of 2-compartment model for the evaluation of indoor radon pollution in a house. Effort on the development of such model is directed towards the prediction of the generation and transfer of radon in indoor air released from groundwater. The model is used to estimate a quantitative daily human exposure through inhalation of such radon based on exposure scenarios. However, prediction from the model has uncertainty propagated from uncertainties in model parameters. In order to assess how model predictions are affected by the uncertainties of model inputs, the study performs a quantitative uncertainty analysis in conjunction with the developed model. An importance analysis is performed to rank input parameters with respect to their contribution to model prediction based on the uncertainty analysis. The results obtained from this study would be used to the evaluation of human risk by inhalation associated with the indoor pollution by radon released from groundwater.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권7호
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• pp.531-535
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• 2004

A new method is presented to construct a classifier. This was accomplished by combining a generalized regression neural network (GRNN) and a genetic algorithm (GA). The classifier constructed in this way is referred to as a GA-GRNN. The GA played a role of controlling training factors simultaneously. The GA-GRNN was applied to classify 4 different Promoter sequences. The training and test data were composed of 115 and 58 sequence patterns, respectively. The classifier performance was investigated in terms of the classification sensitivity and prediction accuracy. Compared to conventional GRNN, GA-GRNN significantly improved the total classification sensitivity as well as the total prediction accuracy. As a result, the proposed GA-GRNN demonstrated improved classification sensitivity and prediction accuracy over the convention GRNN.