• Title/Summary/Keyword: 수치 예측 알고리즘

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An Equivalent Multi-Phase Similitude Law for Pseudodynamic Test on Small-scale RC Models (RC 축소모형의 유사동적실험을 위한 Equivalent Multi-Phase Similitude Law)

  • ;;;Guo, Xun
    • Journal of the Earthquake Engineering Society of Korea
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    • v.7 no.6
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    • pp.101-108
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    • 2003
  • Small-scale models have been frequently used for experimental evaluation of seismic performance because of limited testing facilities and economic reasons. However, there are not enough studies on similitude law for analogizing prototype structures accurately with small-scale models, although conventional similitude law based on geometry is not well consistent in the inelastic seismic behavior. When fabricating prototype and small-scale model of reinforced concrete structures by using the same material. added mass is demanded from a volumetric change and scale factor could be limited due to size of aggregate. Therefore, it is desirable that different material is used for small-scale models. Thus, a modified similitude law could be derived depending on geometric scale factor and equivalent modulus ratio. In this study, compressive strength tests are conducted to analyze equivalent modulus ratio of micro-concrete to normal-concrete. Equivalent modulus ratios are divided into multi phases, which are based on ultimate strain level. Therefore, an algorithm adaptable to the pseudodynamic test. considering equivalent multi-phase similitude law based on seismic damage levels, is developed. In addition, prior to the experiment. it is verified numerically if the algorithm is applicable to the pseudodynamic test.

Performance and structural analysis of a radial inflow turbine for the organic Rankine cycle (유기랭킨사이클용 반경류 터빈의 성능 및 구조 해석)

  • Kim, Do-Yeop;Kim, You-Taek
    • Journal of Advanced Marine Engineering and Technology
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    • v.40 no.6
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    • pp.484-492
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    • 2016
  • The turbine is an important component and has a significant impact on the thermodynamic efficiency of the organic Rankine cycle. A precise preliminary design is essential to developing efficient turbines. In addition, performance analysis and structural analysis are needed to evaluate the performance and structural safety. However, there are only a few exclusive studies on the development process of the radial inflow turbines for the organic Rankine cycle (ORC). In this study, a preliminary design of the ORC radial inflow turbine was performed. Subsequently, the performance and structural analysis were also carried out. The RTDM, which was developed as an in-house code, was used in the preliminary design process. The results of the performance analysis were found to be in good agreement with target performances. Structural analysis of the designed turbine was also carried out in order to determine whether the material selection for this study is suitable for the flow conditions of the designed turbine, and it was found that the selected aluminum alloy is suitable for the designed turbine. However, the reliability of the preliminary design algorithms and numerical methods should be strictly verified by an actual experimental test.

분포형 수문매개변수 산정을 위한 GIS의 활용 - 금강상류유역을 중심으로 -

  • 정승권;정동양
    • Proceedings of the Korea Water Resources Association Conference
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    • 2004.05b
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    • pp.809-813
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    • 2004
  • 강우시 유역 내에서 발생하는 수문특성을 구명하고자 하는 연구는 지속적으로 진행되고 있다. 특히 최근 몇년간 집중호우로 인한 홍수피해가 매우 실각한 수준으로 발생하였고, 이에 지방 소하천을 포함한 전국의 하천정비사업이 새로운 설계홍수빈도를 토대로 진행되고 있다. 우리나라의 강우특성은 여름철에 편중되는 특성을 지니고 있어 홍수시의 홍수방어 대책 등 치수에 많은 어려움이 있는 것이 현실이다. 집중호우로 인한 피해는 전 세계적인 문제로 제기되고 있으며, 이에 강우-유출 관계를 규명하고자 하는 노력이 지속적으로 이루어지고 있다. 강우-유출과정은 시간적, 공간적 다변성을 지닌 수문학적 인자에 의해 좌우되기 때문에 이러한 문제를 해결하기 위해 다년간의 강우-유출 자료를 바탕으로 알고리즘을 생성하고, 이를 바탕으로 정확한 모의가 가능한 수문 모형 및 시스템들을 개발하는데 노력을 기울이고 있다(심순보 등, 1998, 신사철 등, 2002). 그러나 이러한 모형들은 많은 매개변수와 다양한 정보들을 필요로 하게 되어 이들을 처리하는데 많은 어려움이 따른다. 따라서 최근에는 GIS(Geographical Information System)를 활용하여 유역과 분수계를 결정하고 하천형태학적인 특성인자를 추출하는 자동화된 유역정보 추출기술 개발에 대한 관심이 집중되고 있다(Bhaskar, 1992, Francisco, 1995, Yeon, 1999). 이에 본 연구에서는 GIS기법을 이용하여 지형자료로부터 하천연장, 배수면적, 지체시간, 도달시간 등 유역내의 분포형 수문매개변수를 추출하였고 추출된 매개변수를 통해 강우-유출식을 적용하여 분포형 유출량을 산정하는데 활용하고자 한다.ansverse Mercatro) 지구좌표계의 DEM 자료로 변환하였다. 또한 유역의 고도차를 이용한 흐름특성 분석을 위해 수치고도자료를 이용하여 유역흐름특성을 분석할 수 있는 TOPAZ(Topographic PArameteri-Zation) 프로그램을 이용하였다. TOPAZ 프로그램을 통해 분석된 각 격자별 분포형 수문 매개변수는 적합한 관계식을 통해 분포형 유출량을 모의하는데 적용된다.다 정확한 유입량 예측이 가능할 것으로 사료된다.이 작은 오차를 발생하였으며, 전체적으로 퍼프 모형이 입자모형보다는 훨씬 적은 수의 계산을 통해서도 작은 오차를 나타낼 수 있다는 것을 알 수 있었다. 그러나 Gaussian 분포를 갖는 퍼프모형은 전단흐름에서의 긴 유선형 농도분포를 모의할 수 없었고, 이에 관한 오차는 전단계수가 증가함에 따라 비선형적으로 증가하였다. 향후, 보다 다양한 흐름영역에서 장${\cdot}$단점 분석 및 오차해석을 수행한 후에 각각의 Lagrangian 모형의 장점만을 갖는 모형결합 방법을 제시할 수 있을 것으로 판단된다.mm/$m^{2}$로 감소한 소견을 보였다. 승모판 성형술은 전 승모판엽 탈출증이 있는 두 환아에서 동시에 시행하였다. 수술 후 1년 내 시행한 심초음파에서 모든 환아에서 단지 경등도 이하의 승모판 폐쇄 부전 소견을 보였다. 수술 후 조기 사망은 없었으며, 합병증으로는 유미흉이 한 명에서 있었다. 술 후 10개월째 허혈성 확장성 심근증이 호전되지 않아 Dor 술식을 시행한 후 사망한 예를 제외한 나머지 6명은 특이 증상 없이 정상 생활 중이다 결론: 좌관상동맥 페동맥이상 기시증은 드물기는 하나, 영유

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High Resolution Gyeonggi-do Agrometeorology Information Analysis System based on the Observational Data using Local Analysis and Prediction System (LAPS) (LAPS와 관측자료를 이용한 고해상도 경기도 농업기상정보 분석시스템)

  • Chun, Ji-Min;Kim, Kyu-Rang;Lee, Seon-Yong;Kang, Wee-Soo;Park, Jong-Sun;Yi, Chae-Yon;Choi, Young-Jean;Park, Eun-Woo;Hong, Sun-Sung
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.14 no.2
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    • pp.53-62
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    • 2012
  • Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.

Improvement on L-THIA ACN-WQ model for expanded application to the watersheds (유역 확대 적용을 위한 L-THIA ACN-WQ 모형의 개선)

  • Kum, Donghyuk;Park, Youn Shik;Ryu, Jichul;Jeon, Ji-Hong;Lim, Kyoung Jae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.315-315
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    • 2018
  • L-THIA ACN-WQ 2016 모형 개선 연구에서는 침투량 산정, 다중 기상지점 등 유역 규모 확대를 목적으로 엔진 개선과 모형의 최적 매개변수 선정을 위해 최적화 알고리즘을 활용한 자동보정 모듈을 개발하였다. 개선된 침투량 초기손실 산정 계수를 적용한 침투량 산정 방법을 Green-Ampt 모형의 침투량 산정 결과와 비교한 결과 편차는 매우 작았으며, Green-Ampt 모형을 통해 산정된 침투량 범위 내에 분포되어 개선된 침투량 산정 방법의 결과가 유효한 값을 의미하는 것으로 나타났다. 이렇게 도출된 초기손실 산정 계수를 관계식으로 개발하여 L-THIA ACN-WQ 2018 모형 내에서 CN에 따른 초기손실량이 산정되도록 하였고, 이를 기반으로 침투량 및 기저유출량이 산정된다. 유역 규모 확대를 위해 다중 기상지점이 적용되도록 엔진 코드를 개선하였으며, 평창A와 고부A 유역을 대상으로 단일 기상지점과 다중 기상지점 적용에 따른 유출 해석을 유량지속곡선을 통해 비교 한 결과 다중 기상지점 적용에 따라서 평창A와 고부A 유역 모두 유황구간이 크게 달라지는 것으로 나타났다. 특히 고부A 유역은 우황 변동 특성이 크게 나타났는데, 지역적 강우 특성이 뚜렷한 유역에서는 유출해석에 매우 중요한 영향인자로 작용되는 것으로 알 수 있었다. 마지막으로 L-THIA ACN-WQ 2018모형을 이용함에 있어 유역 특성에 알맞은 최적 매개변수 산정을 위해 유량 및 TN, TP 자동보정 툴을 개발하였다. 자동보정툴은 2개의 보정방안으로 개발하였다. 첫 번째는 유역 전체에 대해 하나의 최적매개변수를 도출하는 것이며, 두번째는 유역 내 다중 보정 지점을 통해 소유역별 최적매개변수를 도출하는 것이다. 이를 통해 사용자는 모형의 활용 목적 및 가용 가능한 보정 자료 등을 고려하여 모형의 최적 매개변수를 도출할 수 있다. 이렇게 개선된 L-THIA ACN-WQ 2018 모형을 총량단위유역 한강 평창A와 금강 고부A에 적용한 결과 유량은 NSE 0.76, 0.85로 매우 높게 나타났으며, TN, TP의 NSE는 0.64 ~ 0.86 로 매우 높은 적용성 결과가 도출되었다. Ryu(2016)의 연구 결과와 비교해보면 평창A는 NSE와 $R^2$ 수치로는 큰 차이를 보이지 않았지만, 유량 모의에서 일별 예측값 변화 폭에 큰 변화가 있는 것으로 나타났다. 기존 L-THIA ACN-WQ 2016모형 결과에서는 일별 유량의 변동성이 매우 크지만, L-THIA ACN-WQ 2018 모형에서는 일별 유량 변동폭이 크게 감소하여, 유량 모의에 큰 개선 효과가 있는 것으로 나타났다

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Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.155-175
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    • 2017
  • As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

Optimum Design of Soil Nailing Excavation Wall System Using Genetic Algorithm and Neural Network Theory (유전자 알고리즘 및 인공신경망 이론을 이용한 쏘일네일링 굴착벽체 시스템의 최적설계)

  • 김홍택;황정순;박성원;유한규
    • Journal of the Korean Geotechnical Society
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    • v.15 no.4
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    • pp.113-132
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    • 1999
  • Recently in Korea, application of the soil nailing is gradually extended to the sites of excavations and slopes having various ground conditions and field characteristics. Design of the soil nailing is generally carried out in two steps, The First step is to examine the minimum safety factor against a sliding of the reinforced nailed-soil mass based on the limit equilibrium approach, and the second step is to check the maximum displacement expected to occur at facing using the numerical analysis technique. However, design parameters related to the soil nailing system are so various that a reliable design method considering interrelationships between these design parameters is continuously necessary. Additionally, taking into account the anisotropic characteristics of in-situ grounds, disturbances in collecting the soil samples and errors in measurements, a systematic analysis of the field measurement data as well as a rational technique of the optimum design is required to improve with respect to economical efficiency. As a part of these purposes, in the present study, a procedure for the optimum design of a soil nailing excavation wall system is proposed. Focusing on a minimization of the expenses in construction, the optimum design procedure is formulated based on the genetic algorithm. Neural network theory is further adopted in predicting the maximum horizontal displacement at a shotcrete facing. Using the proposed procedure, various effects of relevant design parameters are also analyzed. Finally, an optimized design section is compared with the existing design section at the excavation site being constructed, in order to verify a validity of the proposed procedure.

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A Study on the Retrieval of River Turbidity Based on KOMPSAT-3/3A Images (KOMPSAT-3/3A 영상 기반 하천의 탁도 산출 연구)

  • Kim, Dahui;Won, You Jun;Han, Sangmyung;Han, Hyangsun
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1285-1300
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    • 2022
  • Turbidity, the measure of the cloudiness of water, is used as an important index for water quality management. The turbidity can vary greatly in small river systems, which affects water quality in national rivers. Therefore, the generation of high-resolution spatial information on turbidity is very important. In this study, a turbidity retrieval model using the Korea Multi-Purpose Satellite-3 and -3A (KOMPSAT-3/3A) images was developed for high-resolution turbidity mapping of Han River system based on eXtreme Gradient Boosting (XGBoost) algorithm. To this end, the top of atmosphere (TOA) spectral reflectance was calculated from a total of 24 KOMPSAT-3/3A images and 150 Landsat-8 images. The Landsat-8 TOA spectral reflectance was cross-calibrated to the KOMPSAT-3/3A bands. The turbidity measured by the National Water Quality Monitoring Network was used as a reference dataset, and as input variables, the TOA spectral reflectance at the locations of in situ turbidity measurement, the spectral indices (the normalized difference vegetation index, normalized difference water index, and normalized difference turbidity index), and the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived atmospheric products(the atmospheric optical thickness, water vapor, and ozone) were used. Furthermore, by analyzing the KOMPSAT-3/3A TOA spectral reflectance of different turbidities, a new spectral index, new normalized difference turbidity index (nNDTI), was proposed, and it was added as an input variable to the turbidity retrieval model. The XGBoost model showed excellent performance for the retrieval of turbidity with a root mean square error (RMSE) of 2.70 NTU and a normalized RMSE (NRMSE) of 14.70% compared to in situ turbidity, in which the nNDTI proposed in this study was used as the most important variable. The developed turbidity retrieval model was applied to the KOMPSAT-3/3A images to map high-resolution river turbidity, and it was possible to analyze the spatiotemporal variations of turbidity. Through this study, we could confirm that the KOMPSAT-3/3A images are very useful for retrieving high-resolution and accurate spatial information on the river turbidity.