• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.131-131
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• 2011

기후변화로 인한 기상이변 현상이 빈번하게 발생하면서 홍수와 같은 자연재해의 피해규모가 증가하고 있다. 이를 극복하기 위해 최근에는 구조적 대책뿐만 아니라 홍수예측시스템과 같은 비구조적 대책에도 많은 관심과 연구가 이루어지고 있다. 통상 홍수예측을 위해서는 예측강우의 정확도가 중요하게 부각되지만 중규모 이상의 유역에서는 수 시간의 지체시간 효과로 인해 AWS 실황강우만으로도 어느정도 선행시간에 대해서 하천유량예측이 가능하다고 할 수 있다. 본 연구에서는 기상청 AWS 실황강우를 이용하여 하천유량을 예측할 경우 어느정도 선행시간과 정확도를 확보할 수 있는지에 대해서 분석하고자 한다. 분석을 위한 시단위 강우자료와 기상자료는 각각 AWS와 ASOS 자료를 이용하였다. 또한 하천유량 모의를 위한 강우-유출모형으로는 SURF 모델(Sejong University River Forecast Model)을 이용하였다. 이 모형은 저류함수모형 기반의 연속형 강우-유출모형으로 미래에 대한 유출모의결과의 정확도를 향상시키기 위해 앙상블 칼만필터링 기법을 연계한 모형이다. 그림 1은 충주댐유역에 대해서 2009.7.8~17일(240시간)에 대해서 관측유량 자료동화 전후의 결과를 나타낸 것이다. 현시점을 100, 105, 110, 115시간으로 가정하고 미래기간에 대해서는 관측강우를 0으로 가정했을 때 대략 첨두유량 발생 5시간 전에 예측된 모의유량이 관측유량과 거의 일치함을 확인할 수 있다. 따라서 실황강우와 관측유량 자료동화 기법을 연계할 경우 수 시간의 선행시간에 대해서 유량예측이 가능한 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.209-213
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• 2007

최근 우리나라에서는 기상이변과 기후변화에 의한 국지성 집중호우의 발생으로 인해 인명 및 재산 피해가 증가하고 있고, 특히 도시지역의 경우 산업화와 도시화로 인한 홍수량 및 첨두홍수량이 뚜렷하게 증가하고 있는 것으로 나타나고 있다. 이에 따라 기후변화와 도시화 등을 고려한 확률수문량의 재산정이 요구되고 있으며, 이를 위한 한 방법으로 지역빈도해석(regional frequency analysis)에 대한 연구가 꾸준히 진행되고 있으나 도시유역에 대한 지역빈도해석에 관한 연구는 미비한 실정이다. 따라서 본 연구에서는 도시지역에 대한 지역빈도해석의 적용성을 검토하기 위해 주요 도시유역을 분석대상으로 선정하고, 해당 도시유역 내의 AWS(Automatic Weather System) 자료를 수집한다. 대상지역의 AWS 자료를 구축한 후, 각각의 자료에 대해 대표적인 지역빈도해석 기법 중의 하나인 홍수지수법(Index Flood Method)을 적용하여 확률강우량을 산정하고 지점빈도해석 결과와 비교하여 도시유역에 대한 지역빈도해석의 적용성을 판단하고자 한다. 대상지역에 대한 홍수지수법의 적용결과를 살펴보면, 지점빈도해석에 의한 확률강우량보다 홍수지수법에 의해 산정된 확률강우량이 작게 추정되는 것으로 나타났다.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1051-1059
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• 2008

In the development process of an ECU (Electrical Control Unit), numerous tests are necessary to evaluate the performance and control algorithm. The vehicle based test is expensive and requires long time. Also, it is difficult to guarantee the safety of the test driver. To overcome the various problems faced in the development process, the ECU test has been done using HIL (Hardware In the Loop). The HIL environment has the actual hardware including an ECU and a virtual vehicle model. In this paper, the test platform environment is devloped for the AWS ECU black box test. The test platform is built on HIL (Hardware In the Loop) architecture. Using the developed test platform, the control algorithm of the AWS ECU can be evaluated under the virtual driving condition of the bi-modal tram. Driving conditions, such as a front steering angle and vehicle velocity, are defined through the PC (Personal Computer) input. Input signals are transformed to electrical signals in the PC. These signals become the input conditions of the AWS ECU. The AWS ECU is stimulated by arbitory input conditons, and responses of the system are observed.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.319-326
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• 2002

Rainfall estimation was conducted based on TRMM-PR/VIES and GMS data. AWS rainfall data were used for various validation. General procedure is as follows; 1) Z-R relationship was made by the comparison of TRMM-PR and AWS data. 2) new algorithm was developed by the estimates from Z-R equation and TBB of VIRS. 3) rainfall was estimated through the substitution of GMS data for TBB of VIRS in the newly developed algorithm. Z-R relationship based on TRMM is $Z=303R^{0.72}$ with correlation coefficient 0.57. The newly developed algorithm is shown as correlation coefficient 0.67 and RMSE 17mm/hr. New algorithm shows the underestimating tendency in case of heavy rainfall event.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.943-944
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• 2023

본 프로젝트는 AWS 에서 제공되는 AI/ML 플랫폼과 LLM 모델을 기반으로 문서 및 텍스트와 ppt 를 자동 변환하는 서비스로, 실생활 및 업무에서 활용이 가능하며 별도 사용자 조작 없이 사용가능한 발표자료 및 대본 제작 도구를 통해 일의 효율성을 향상시키고자 한다.

• Journal of Environmental Impact Assessment
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• v.11 no.2
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• pp.109-116
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• 2002

The diagnostic and prognostic methods for generating 3 dimensional wind field were comparatively analyzed and 4 dimensional data assimilation (FDDA) technique by incorporating Automatic Weather System (AWS) into the prognostic methods was discussed for the urban scale air quality model. The A WS covered the urban scale grid distance of 10.6 km and 4.3 km in South Korea and Kyong-in region, respectively. This is representing that AWS for FDDA could be fairly well accommodated in prognostic model with the meso${\gamma}$~ microa scale (~5 km), indicating that the 3 dimensional wind field by FDDA technique could be a useful interpretative tool in urban area for the atmospheric environmental impact assessment.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.1321-1325
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• 2004

The continuous monitoring of the runoff in the small-scaled urban watershed and easily accessible experiment catchment is necessary to investigate the overall status of the development in the urban catchment and the varying aspects of the discharge characteristics due to the urbanization. However, the research on the management and the characteristics of the small-scaled model basin for discharge tests has not been actively performed up to now. This study selects the Dong-Eui university basin, which locates at Gaya-dong in Busan, as the experiment catchment to monitor the discharge rate in the urban watershed. EMS(DEMS, DATA-PCS EMS, mini rain gage & AWS(AWS-DEU, DATA-PCS AWS) monitoring system installed for the collection of hydrological data such as the rainfall and the waterlevel. This experiment catchment is the typical urban catchment and is under development, and it is possible to analyze the varying aspects of the discharge rate during and after the development.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.395-397
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• 2010

AWS that exist in Pusan is watching local meteorological phenomena established in place that the weather observatory does not exist by real time, and is used usefully to early input data of numerical weather forecasting model. I wished to display downtown of Pusan and air temperature change of peripheral area using this AWS data. Analyzed volatility using AWS observation data for 5 years to recognize air temperature change of Pusan area through data about temperature among them. Drew air temperature distribution chart by season of recapitulative Pusan area applying IDW linear interpolation with this.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.25-33
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• 2013

All-wheel steering (AWS) system is applied to articulated vehicles to reduce turning radius. The swing-out suppression algorithm is applied to AWS ECU, a key component of AWS system. The swing-out suppression algorithm applied to AWS ECU has a problem when velocity of vehicle is changed. In this paper, new algorithm based on moving distance that solve velocity problem is proposed. The HILS simulation and the test articulated bus is used to validate algorithm.

• Journal of Industrial Technology
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• v.31 no.A
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• pp.119-122
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• 2011

AWS (Automated Weather Station) wind data was used to predict the annual energy production of Gangwon wind farm having a total capacity of 98 MW in Korea. Two common wind energy prediction programs, WAsP and WindSim were used. Predictions were made for three consecutive years of 2007, 2008 and 2009 and the results were compared with the actual annual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from both prediction programs were close to the actual energy productions and the errors were within 10%.