• Title/Summary/Keyword: Longterm prediction

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Experiments on the Properties and Carbonation of the Longterm-aged Concrete Buildings (장기재령 건축물의 콘크리트 품질 및 중성화에 관한 연구)

  • 김형래;윤상천;윤상렬;김태섭;지남용;이리형
    • Proceedings of the Korea Concrete Institute Conference
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    • 1996.10a
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    • pp.189-195
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    • 1996
  • This study was carried out ont the longterm aged reinforced concrete housings for the prediction of life expectancy and the suggestion of fundamental informations on the durable concrete. In this paper, the durability of concrete is compared with carbonation depth, and the measutrments fo carbonation depth and properties have been made on the number of cores taken from structures. And finally, the relationships between carbonation rate and such properties as strength, absorption ratio, density were examined.

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Regionalized Regression Model for Monthly Streamflow in Korean Watersheds (韓國河川의 月 流出量 推定을 위한 地域化 回歸模型)

  • Kim, Tai-Cheol;Park, Sung-Woo
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.26 no.2
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    • pp.106-124
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    • 1984
  • Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.

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Propeller racing of ocean-going ships with multiple screw propellers (다축선의 프로펠러 레이싱 추정에 관한 연구)

  • Park, Jong-Heon
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.43 no.3
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    • pp.222-231
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    • 2007
  • This paper represents a basic statistical examination on the navigability of ocean-going ship from the point of estimating the time lasting period when propeller racing occurred by using the basic probability theory and the statistics. The propeller racing is one of the most important seakeeping qualities in relation to the safety of the main engine and shafting system. The trend of the racing has been mainly investigated in order to estimate allowable maximum propeller diameter, operation of ocean-going ships, etc.. In those studies, the propeller racing generally and mainly means the situation (propeller exposed) in which the relative motion amplitude between ship hull and wave surface would exceed a depth of point in rotary disk propeller. Therefore, it seems that the magnitude of the amplitude and its exceeding frequency of propeller racing have been examined as a principal subject of study as usual. However, the time during which the amplitude exceeds the depth of point, that is, the propeller exposes in the air, must be also one of most important factor affecting the trend of propeller racing. Then, this paper proposes a new practical method for estimating the time lasting of exposed propeller related to propeller racing in rough-confused seas on the basis of the linear strip theory and the statistics. And, numerical examples of estimating the propeller racing probability are given for four wide ship forms. Finally the usefulness of the proposed method for predicting propeller racing based on the time lasting period is discussed.

The long-term agricultural weather forcast methods using machine learning and GloSea5 : on the cultivation zone of Chinese cabbage. (기계학습과 GloSea5를 이용한 장기 농업기상 예측 : 고랭지배추 재배 지역을 중심으로)

  • Kim, Junseok;Yang, Miyeon;Yoon, Sanghoo
    • Journal of Digital Convergence
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    • v.18 no.4
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    • pp.243-250
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    • 2020
  • Systematic farming can be planned and managed if long-term agricultural weather information of the plantation is available. Because the greatest risk factor for crop cultivation is the weather. In this study, a method for long-term predicting of agricultural weather using the GloSea5 and machine learning is presented for the cultivation of Chinese cabbage. The GloSea5 is a long-term weather forecast that is available up to 240 days. The deep neural networks and the spatial randomforest were considered as the method of machine learning. The longterm prediction performance of the deep neural networks was slightly better than the spatial randomforest in the sense of root mean squared error and mean absolute error. However, the spatial randomforest has the advantage of predicting temperatures with a global model, which reduces the computation time.

Long-Term Science Goals with In Situ Observations at the Sun-Earth Lagrange Point L4

  • Dae-Young Lee;Rok-Soon Kim;Kyung-Eun Choi;Jungjoon Seough;Junga Hwang;Dooyoung Choi;Ji-Hyeon Yoo;Seunguk Lee;Sung Jun Noh;Jongho Seon;Kyung-Suk Cho;Kwangsun Ryu;Khan-Hyuk Kim;Jong-Dae Sohn;Jae-Young Kwak;Peter H. Yoon
    • Journal of Astronomy and Space Sciences
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    • v.41 no.1
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    • pp.1-15
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    • 2024
  • The Korean heliospheric community, led by the Korea Astronomy and Space Science Institute (KASI), is currently assessing the viability of deploying a spacecraft at the Sun-Earth Lagrange Point L4 in collaboration with National Aeronautics and Space Administration (NASA). The aim of this mission is to utilize a combination of remote sensing and in situ instruments for comprehensive observations, complementing the capabilities of the L1 and L5 observatories. The paper outlines longterm scientific objectives, underscoring the significance of multi-point in-situ observations to better understand critical heliospheric phenomena. These include coronal mass ejections, magnetic flux ropes, heliospheric current sheets, kinetic waves and instabilities, suprathermal electrons and solar energetic particle events, as well as remote detection of solar radiation phenomena. Furthermore, the mission's significance in advancing space weather prediction and space radiation exposure assessment models through the integration of L4 observations is discussed. This article is concluded with an emphasis on the potential of L4 observations to propel advancements in heliospheric science.

Exploration and Application of Regulatory PM10 Measurement Data for Developing Long-term Prediction Models in South Korea (PM10 장기노출 예측모형 개발을 위한 국가 대기오염측정자료의 탐색과 활용)

  • Yi, Seon-Ju;Kim, Ho;Kim, Sun-Young
    • Journal of Korean Society for Atmospheric Environment
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    • v.32 no.1
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    • pp.114-126
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    • 2016
  • Many cohort studies have reported associations of individual-level long-term exposures to $PM_{10}$ and health outcomes. Individual exposures were often estimated by using exposure prediction models relying on $PM_{10}$ data measured at national regulatory monitoring sites. This study explored spatial and temporal characteristics of regulatory $PM_{10}$ measurement data in South Korea and suggested $PM_{10}$ concentration metrics as long-term exposures for assessing health effects in cohort studies. We obtained hourly $PM_{10}$ data from the National Institute of Environmental Research for 2001~2012 in South Korea. We investigated spatial distribution of monitoring sites using the density and proximity in each of the 16 metropolitan cities and provinces. The temporal characteristics of $PM_{10}$ measurement data were examined by annual/seasonal/diurnal patterns across urban background monitoring sites after excluding Asian dust days. For spatial characteristics of $PM_{10}$ measurement data, we computed coefficient of variation (CV) and coefficient of divergence (COD). Based on temporal and spatial investigation, we suggested preferred long-term metrics for cohort studies. In 2010, 294 urban background monitoring sites were located in South Korea with a site over an area of $415.0km^2$ and distant from another site by 31.0 km on average. Annual average $PM_{10}$ concentrations decreased by 19.8% from 2001 to 2012, and seasonal $PM_{10}$ patterns were consistent over study years with higher concentrations in spring and winter. Spatial variability was relatively small with 6~19% of CV and 21~46% of COD across 16 metropolitan cities and provinces in 2010. To maximize spatial coverage and reflect temporal and spatial distributions, our suggestion for $PM_{10}$ metrics representing long-term exposures was the average for one or multiple years after 2009. This study provides the knowledge of all available $PM_{10}$ data measured at national regulatory monitoring sites in South Korea and the insight of the plausible longterm exposure metric for cohort studies.

The Change of Industrial Distribution Pattern by Worker Status Classification : Busan, 1994~2004 (종사상 지위분류에 따른 산업분포변화: 부산, 1994~2004)

  • Kang, In-Joo;Nam, Kwang-Woo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.4
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    • pp.111-121
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    • 2007
  • Diagnosis and Prediction of urban industrial structure is a key subject for establishment of sustainable urban development plan. By this time, studies of industry-related urban spatial structure have been concentrated on measurement of space distribution by industry type mainly using data about urban industries or total worker numbers. Now, status of workers become an important issue so this study analyzed qualitative change of urban industrial structure in the view of space using work status classification system. For that, data for work status in 1994 and 2004 were collected in towns and villages, and space analysis units were coincided based on change data between 1994 and 2004. Then, it analyzed spatial distribution pattern of employment through qualitative standard called work status using GIS. The analysis results by work status type of Busan industrial structure in GIS circumstance were as below. First, traditional labor intensive industries met a limit and service and wholesale/retail sale industries went to be poor livelihood. Therefore, Busan's employment rate should be decreased and worker numbers were statistically increased, however, irregular and non-wage workers were suddenly increased. So, it was determined that the quality of employment in Busan area came down. Second, a traditional downtown area has dwindled; on the other hand, employment has been increased in new town or new industrial complex and in the area developed services rather than the manufacturing industry. It is expected that the result of this study may be meaningful as data to prepare for longterm industrial development plan through qualitative evaluation called work status as well as to make behavior pattern of industrial structure which is basis of urban development.

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