• Atmosphere
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• v.28 no.2
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• pp.163-174
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• 2018

In order to assimilate MHS satellite data into the convective scale model at KMA, ATOVS data are reprocessed to utilize the original high-resolution data. And then to improve the preprocessing experiments for cloud detection were performed and optimized to convective-scale model. The experiment which is land scattering index technique added to Observational Processing System to remove contaminated data showed the best result. The analysis fields with assimilation of MHS are verified against with ECMWF analysis fields and fit to other observations including Sonde, which shows improved results on relative humidity fields at sensitive level (850-300 hPa). As the relative humidity of upper troposphere increases, the bias and RMSE of geopotential height are decreased. This improved initial field has a very positive effect on the forecast performance of the model. According to improvement of model field, the Equitable Threat Score (ETS) of precipitation prediction of $1{\sim}20mm\;hr^{-1}$ was increased and this impact was maintained for 27 hours during experiment periods.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1712-1716
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• 2008

Performance of ground improvement project using prefabricated vertical drains of condition, in which approximately 10m dredged fill overlies original soft foundation layer in the coastal area has been conducted. From field monitoring results, excessive ground settlement compared to predicted settlement in design stage developed during the following one year. In order to predict the final consolidation behavior, recalculation of consolidation settlements and back analysis using observed settlements were conducted. Field monitoring results of surface settlements were evaluated, and then corrected because large shear deformation was occurred by construction events in the early stages of consolidation. To predict the consolidation behavior, material functions and in-situ conditions from laboratory consolidation test were re-analyzed. Using these results, height of additional embankment is estimated to satisfy residual settlement limit and maintain an adequate ground elevation. The recalculated time-settlement curve has been compared to field monitoring results after additional surcharge was applied.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.43-55
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• 2015

In the case of satellite navigation positioning, the shielding of satellite signals is determined by the environment of the region at which a user is located, and the navigation performance is determined accordingly. The accuracy of user position determination varies depending on the dilution of precision (DOP) which is a measuring index for the geometric characteristics of visible satellites; and if the minimum visible satellites are not secured, position determination is impossible. Currently, the GLObal NAvigation Satellite system (GLONASS) of Russia is used to supplement the navigation performance of the Global Positioning System (GPS) in regions where GPS cannot be used. In addition, the European Satellite Navigation System (Galileo) of the European Union, the Chinese Satellite Navigation System (BeiDou) of China, the Quasi-Zenith Satellite System (QZSS) of Japan, and the Indian Regional Navigation Satellite System (IRNSS) of India are aimed to achieve the full operational capability (FOC) operation of the navigation system. Thus, the number of satellites available for navigation would rapidly increase, particularly in the Asian region; and when integrated navigation is performed, the improvement of navigation performance is expected to be much larger than that in other regions. To secure a stable and prompt position solution, GPS-GLONASS integrated navigation is generally performed at present. However, as available satellite navigation systems have been diversified, finding the minimum satellite constellation combination to obtain the best navigation performance has recently become an issue. For this purpose, it is necessary to examine and predict the navigation performance that could be obtained by the addition of the third satellite navigation system in addition to GPS-GLONASS. In this study, the current status of the integrated navigation performance for various satellite constellation combinations was analyzed based on 2014, and the navigation performance in 2020 was predicted based on the FOC plan of the satellite navigation system for each country. For this prediction, the orbital elements and nominal almanac data of satellite navigation systems that can be observed in the Korean Peninsula were organized, and the minimum elevation angle expecting signal shielding was established based on Matlab and the performance was predicted in terms of DOP. In the case of integrated navigation, a time offset determination algorithm needs to be considered in order to estimate the clock error between navigation systems, and it was analyzed using two kinds of methods: a satellite navigation message based estimation method and a receiver based method where a user directly performs estimation. This simulation is expected to be used as an index for the establishment of the minimum satellite constellation for obtaining the best navigation performance.

• Explosives and Blasting
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• v.22 no.3
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• pp.43-55
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• 2004

Use term of tower style construction exceeds recently. Accordingly, according to construction safety diagnosis result, achieve removal or Improvement construction. But when work removal, must shorten shut down time. Therefore, removal method of construction to use blasting demolition of construction is very profitable. Influence construction and equipment by blasting vibration and occurrence vibration caused by felling impact. Is using disadvantageous machine removal method of construction by and economic performance by effect of such vibartion. Therefore, this research studied techniques to forecast vibartion level happened at blasting demolition and vibration reduction techniques by use a scaled model test.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.315-320
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• 2004

Swing check valves are the most common type of check valve in nuclear power plant and need to be operated property to perform their functions and to keep the valve internals stable. However, for a swing check valve disc to remain stable, the opening characteristics should be identified and the upstream flow velocity should be enough to hold the disc fully open and without motion. Thus it is necessary to develop a model for predicting the flow velocity for a given disc opening. In the present study, the disc positions with mean flow velocity were measured for 3 inch and 6 inch swing check valves. Comparison of the measurements with the existing models showed that the models underestimate the mean flow velocity for a given disc position. Therefore, the existing model for predicting swing check valve disc position was improved with the realistic disc impingement area perpendicular to the flow stream and the experimental data. The result showed that the improved model with the best estimate of kb = 0.04 predicts well the disc openings of 6 inch swing check valve, especially in the low velocity region. For better prediction of the disc opening at high flow velocity, however, it is recommended to develop a kb correlation with the disc angle.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.800-807
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• 2010

Jack knifing accident of semi trailer vehicle is one of the most dangerous accident type because the vehicle cross over its lane by the accident. Jack knifing accident can be predicted and detected by GNSS precise relative positioning. But integer ambiguity resolution procedure is inevitable in GNSS precise relative positioning. In this paper, success rate improving method of integer ambiguity resolution is proposed for jack knifing accident prediction and detection of semi trailer vehicle, and proposed method is tested by simulation.

• The Journal of the Acoustical Society of Korea
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• v.20 no.5
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• pp.48-53
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• 2001

In speaker verification based on LPC analysis the prediction residues are ignored and LPCC(LPC cepstrum) are only used to compose feature vectors. In this study, LPCC and RCEP (residual cepstrum) extracted from residues are used as feature parameters in the various environmental speaker verification. We propose the weighting function which can enlarge inter-speaker variation by weighting pitch, speaker inherent vector, included in residual cepstrum. Simulation results show that the average speaker verification rate is improved in the rate of 6％ with RCEP and LPCC at the same time and is improved in the rate of 2.45% with the proposed weighted RCEP and LPCC at the same time compared with no weighting.

• Journal of Korean Society for Quality Management
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• v.52 no.3
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• pp.479-493
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• 2024

Purpose: The deterioration in the quality of failure history data due to differences in interpretation of failures among workers at power plants and the lack of consistency in the way failures are recorded negatively impacts the efficient operation of power plants. The purpose of this study is to propose a system that classifies power generation facilities failures consistently based on the failure history text data created by the workers. Methods: This study utilizes data collected from three coal unloaders operated by Korea Midland Power Co., LTD, from 2012 to 2023. It classifies failures based on the results of Soft Voting, which incorporates the prediction probabilities derived from applying the predict_proba technique to four machine learning models: Random Forest, Logistic Regression, XGBoost, and SVM, along with scores obtained by constructing word dictionaries for each type of failure using LIME, one of the XAI (Explainable Artificial Intelligence) methods. Through this, failure classification system is proposed to improve the quality of power generation facilities failure history data. Results: The results of this study are as follows. When the power generation facilities failure classification system was applied to the failure history data of Continuous Ship Unloader, XGBoost showed the best performance with a Macro_F1 Score of 93%. When the system proposed in this study was applied, there was an increase of up to 0.17 in the Macro_F1 Score for Logistic Regression compared to when the model was applied alone. All four models used in this study, when the system was applied, showed equal or higher values in Accuracy and Macro_F1 Score than the single model alone. Conclusion: This study propose a failure classification system for power generation facilities to improve the quality of failure history data. This will contribute to cost reduction and stability of power generation facilities, as well as further improvement of power plant operation efficiency and stability.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.186-186
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• 2022

강수 및 침투 등으로 발생하는 지하수위의 변동을 예측하는 것은 지하수 자원의 활용 및 관리에 필수적이다. 지하수위의 변동은 지하수 자원의 활용 및 관리뿐만이 아닌 홍수 발생과 지반의 응력상태 등에 직접적인 영향을 미치기 때문에 정확한 예측이 필요하다. 본 연구는 인공신경망 중 다층퍼셉트론(Multi Layer Perceptron, MLP)을 이용한 지하수위 예측성능 향상을 위해 MLP의 구조 중 Optimizer를 개량하였다. MLP는 입력자료와 출력자료간 최적의 상관관계(가중치 및 편향)를 찾는 Optimizer와 출력되는 값을 결정하는 활성화 함수의 연산을 반복하여 학습한다. 특히 Optimizer는 신경망의 출력값과 관측값의 오차가 최소가 되는 상관관계를 찾는 연산자로써 MLP의 학습 및 예측성능에 직접적인 영향을 미친다. 기존의 Optimizer는 경사하강법(Gradient Descent, GD)을 기반으로 하는 Optimizer를 사용했다. 하지만 기존의 Optimizer는 미분을 이용하여 상관관계를 찾기 때문에 지역탐색 위주로 진행되며 기존에 생성된 상관관계를 저장하는 구조가 없어 지역 최적해로 수렴할 가능성이 있다는 단점이 있다. 본 연구에서는 기존 Optimizer의 단점을 개선하기 위해 지역탐색과 전역탐색을 동시에 고려할 수 있으며 기존의 해를 저장하는 구조가 있는 메타휴리스틱 최적화 알고리즘을 이용하였다. 메타휴리스틱 최적화 알고리즘 중 구조가 간단한 화음탐색법(Harmony Search, HS)과 GD의 결합모형(HS-GD)을 MLP의 Optimizer로 사용하여 기존 Optimizer의 단점을 개선하였다. HS-GD를 이용한 MLP의 성능검토를 위해 이천시 지하수위 예측을 실시하였으며 예측 결과를 기존의 Optimizer를 이용한 MLP 및 HS를 이용한 MLP의 예측결과와 비교하였다.

• Atmosphere
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• v.29 no.2
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• pp.131-147
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• 2019

On the urban scale, Micro-climate analysis models for urban scale have been developed to investigate the atmospheric characteristics in urban surface in detail and to predict the micro-climate change due to the changes in urban structure. BioCAS (Biometeorological Climate Impact Assessment System) is a system that combines such analysis models and has been implemented internally in the Korea Meteorological Administration. One of role in this system is the analysis of the health impact by heat waves in urban area. In this study, the vegetation cooling models A and B were developed and linked with BioCAS and evaluated by the temperature drop at the vegetation areas during ten selected heat-wave days. Smaller prediction errors were found as a result of applying the vegetation cooling models to the heat-wave days. In addition, it was found that the effects of the vegetation cooling models produced different results according to the distribution of vegetation area in land cover near each observation site - the improvement of the model performance on temperature analysis was different according to land use at each location. The model A was better fitted where the surrounding vegetation ratio was 50% or more, whereas the model B was better where the vegetation ratio was less than 50% (higher building and impervious areas). Through this study, it should be possible to select an appropriate vegetation cooling model according to its fraction coverage so that the temperature analysis around built-up areas would be improved.