• Title/Summary/Keyword: Temperature interpolation

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Experimental Study on the Adsorption Characteristics of Methane Gas Considering Coalbed Depth in Coalbed Methane Reservoirs (석탄층 메탄가스 저류층에서 탄층 심도를 고려한 메탄가스의 흡착 특성에 관한 실험 연구)

  • Chayoung Song;Dongjin Lee;Jeonghwan Lee
    • Journal of the Korean Institute of Gas
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    • v.27 no.2
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    • pp.39-48
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    • 2023
  • This study presents the experimental results to measure the adsorption amount of methane gas by coal according to the conditions of a coalbed methane (CBM) reservoir. Adsorbed gas to coal seam particles was measured under reservoir conditions (normal pressure ~ 1,200 psi pressure range, temperature range15 ~ 45℃) using coal samples obtained from random mines in Kalimantan Island, North Indonesia. The obtained amount of absolute adsorbed gas was applied to triangular with linear interpolation to calculate the maximum amount of adsorbed gas according to temperature and pressure change, at which no experiment was performed. As a result, it was revealed that the amount of adsorbed gas to coal particles increased as the pressure increased and temperature decreased, but the increase of the amount of adsorbed gas decreased at more than an appropriate depth(1,000 ft). In the cleat permeability and cleat porosity for each depth of the coal bed considering the effective stress, the cleat permeability was 28.86 ~ 46.81 md, and the cleat porosity was 0.83 ~ 0.98%. This means that the gas productivity varies significantly with the depth because the reduction of the permeability according to the depth in the coal seam is significant. Therefore, a coalbed depth should be considered essential when designing the spacing of production wells in a coalbed methane reservoir in further study.

Design and Implementation of Concentration Calculation Algorithm for the Infrared Combustible Gas Detector (적외선 가연성 가스검지기의 농도 산출 알고리즘의 설계 및 구현)

  • Han, Seungho;Lyu, Geunjun;Lee, Yeonjae;Kim, Hiesik;Park, Gyoutae
    • Journal of Energy Engineering
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    • v.25 no.1
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    • pp.145-152
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    • 2016
  • Recently, we can find news about toxic and combustible gas accident. So, we have to develop gas detector that can measure gas at dangerous area for preventing gas accidents. In this paper, we calculate a approximation function from sensor's output using the linear regressiong. And we develop software algorithm using Neville's algorithm for measuring gas concentration. Finally, we compare our algorithm with combustible gas detectors that are already developed, by using standard gas samples manufactured Korea Gas Safety. As a result of this experiment, we confirm that performance of our algorithm is more improved than performance of already developed combustible gas detectors. In the future, we'll research how to improve reliability from using count, temperature and humidity. And we'll design hardware applied explosion proof for safety.

The Temporal and Spatial Distribution Analysis of Red Tide using GIS (GIS를 이용한 적조의 시-공간적 분포 분석)

  • Jeong Jong-chul
    • Spatial Information Research
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    • v.13 no.3 s.34
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    • pp.253-260
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    • 2005
  • The aim of this study is to analyze the temporal and spatial distribution aspects of red tide using GIS techniques. The damage caused by red tide appears various aspects according to the species, concentration and spatial distribution of red tide plankton. Therefore, in order to prevent the damage of red tide it is important to understand the distribution characteristics of red tide by each species according to time and space. In this perspective, we analyzed the beginning outbreak area, spatial occurrence frequency and spatial migration of red tide. The spatial data used by this study was constructed by digitizing the red tide quick report and coupled with various attributes such as species, concentration and water temperature for construction of red tide database. We used various spatial analysis methods such as union, intersect, tracking, buffer and spatial interpolation for analyzing temporal and spatial characteristics of red tide. From the result of these spatial analyses, we could get the spatial information on the temporal and spatial distribution characteristics of red tide at the Southern Sea.

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System gamma and color temperature correction in low gray level of LCD device by using PLCC model (PLCC모델을 이용한 시스템감마와 저계조의 색온도 보정방법)

  • Kim, Young-Kook;Dhamija, Rohit;Jeon, Byeung-Woo
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.262-263
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    • 2008
  • LCD 디바이스는 그 동작원리와 전기-광학적 특성에 의해 CRT와는 다른 감마곡선 특성을 갖고 있다. 대부분의 LCD디스플레이 디바이스들의 감마곡선은 CRT와는 달리 일관성을 갖지 않을 뿐 더러 흑백계조입력을 기준으로 하는 감마보정을 위해 RED, GREEN, BLUE 입력값을 세부적으로 조정할 때 각 계조입력에 대한 상관색온도가 일정한 값을 갖지 않아 LCD의 특성에 대한 모델링과 보정에 어려움이 있다. 또한, 애플사의 맥머신 그리고 실리콘 그래픽스사의 시스템과 같이 소정의 감마값을 전제로 해당 시스템의 내부참조테이블(internal look-up table)이 설계되어 각기 다른 시스템감마를 가지는 장치들에 의해 인코딩되어진 영상출력신호의 경우, 동일한 시스템을 갖추거나 시스템감마에 대한 역감마특성을 가진 디스플레이장치가 아닌 환경에서는 원본영상에 대한 왜곡은 더욱 커질 수 있다. 특히, 낮은 흑백계조입력에서의 색온도의 경우, 파장에 따라 서로 다른 감쇄성능을 가진 일반적인 컬러필터의 특성에 의한 누설광(light leakage)에 의해 결정되며, 이로 인해 색온도가 특정한 객을 띄는 현상이 발생한다. 본 논문에서는 LCD디스플레이의 감마곡선을 여러 가지 시스템감마에 대응할 수 있는 감마곡선예 일치시키고, 계조선형성을 동시에 개선하기 위하여 입력 디지털값과 삼자극치간 관계를 나타내는 여러 가지 컬러모델링 방법 중에서 PLCC(Piecewise Linear Interpolation assuming Constant Chromaticity coordinates)모델을 적용하고, 목표로 하는 감마곡선과 색온도를 만족하기 위한 새로운 입력값을 구한 후 이를 컬러참조테이블(color look-up table)예 적용하는 방법과 저계조에서의 색온도를 목표색온도에 근접시키는 방법을 제안한다.

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Generation of Meteorological Parameters for Tropospheric Delay on GNSS Signal (GNSS 신호의 대류층 지연오차 보정을 위한 기상 정보 생성)

  • Jung, Sung-Wook;Baek, Jeong-Ho;Jo, Jung-Hyun;Lee, Jae-Won;Park, In-Kwan;Cho, Sung-Ki;Park, Jong-Uk
    • Journal of Astronomy and Space Sciences
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    • v.25 no.3
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    • pp.267-282
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    • 2008
  • The GNSS (Global Navigation Satellite System) signal is delayed by the neutral atmosphere at the troposphere, so that the delay is one of major error sources for GNSS precise positioning. The tropospheric delay is an integrated refractive index along the path of GNSS signal. The refractive index is empirically related to standard meteorological variables, such as pressure, temperature and water vapor partial pressure, therefore the tropospheric delay could be calculated from them. In this paper, it is presented how to generate meteorological data where observation cannot be performed. KASI(Korea Astronomy & Space Science Institute) has operated 9 GPS (Global Positioning System) permanent stations equipped with co-located MET3A, which is a meteorological sensor. Meteorological data are generated from observations of MET3A by Ordinary Kriging. To compensate a blank of observation data, simple models which consider periodic characteristics for meteorological data, are employed.

Projection and Analysis of Future Temperature and Precipitation in East Asia Region Using RCP Climate Change Scenario (RCP 기반 동아시아 지역의 미래 기온 및 강수량 변화 분석)

  • Lee, Moon-Hwan;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.578-578
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    • 2015
  • 동아시아 지역의 대부분은 몬순의 영향으로 인해 수자원의 계절적 변동성이 크며 이로 인해 홍수 및 가뭄이 빈번하게 발생하고 있다. 기후변화에 따른 기온과 강수량의 변화는 수자원의 변동성을 더욱 악화시킬 수 있으며, 수재해 피해를 더욱 가중시킬 것으로 전망되고 있다. 본 연구에서는 기후변화에 따른 동아시아 지역의 기온 및 강수량의 변화를 전망하고, 그 특성을 분석하고자 한다. 이를 위해 CMIP5의 핵심실험인 2개 RCP시나리오(RCP4.5, RCP8.5)에 대한 다수의 GCMs 결과를 이용하였다. 구축한 기후시나리오를 이중선형보간법(bilinear interpolation)을 이용하여 공간적으로 상세화하였으며, Delta method를 이용하여 편의보정을 수행하였다. GCM 모의자료의 편의를 산정하기 위해 관측자료는 APHRODITE의 기온 및 강수량 자료를 이용하였다. GCM에 따라 차이가 나지만, 우리나라의 경우 평균적으로 100~300mm 정도 과소모의 되는 것으로 나타났다. 미래 기온 및 강수량 전망을 위해 과거기간은 1976~2005년, 미래기간은 2021~2050년(2040s), 2061~2090년(2070s)으로 구분하였다. 우리나라의 경우 RCP 4.5 하에서 연평균기온은 $1.4{\sim}1.7^{\circ}C$(2040s), $2.2{\sim}3.4^{\circ}C$(2070s) 정도 상승할 것으로 나타났으며, 연평균 강수량은 4.6~5.3% (2040s), 8.4~10.5% (2070s) 정도 증가할 것으로 나타났다. RCP 8.5에서는 연평균 기온은 RCP4.5에 비해 상승폭이 더 컸으며, 강수량은 유사한 결과가 나타났다. 또한, 동아시아 지역에서도 연평균 기온이 상승하고 연평균 강수량은 증가하는 것으로 나타났다. 다만, 지역별로 계절별 기온 및 강수량이 매우 다른 양상으로 나타났다. 이는 동아시아 지역과 같이 계절별 강수량 발생패턴이 다른 지역에서는 홍수 및 가뭄에 매우 중요한 역할을 할 것이다. 따라서 지역적으로 계절별 강수량의 변화를 분석해야 할 것으로 판단되며, 추후 유출량 모의를 기반으로 홍수 및 가뭄의 영향을 직접적으로 분석해야할 것으로 판단된다.

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Prediction of pollution loads in the Geum River upstream using the recurrent neural network algorithm

  • Lim, Heesung;An, Hyunuk;Kim, Haedo;Lee, Jeaju
    • Korean Journal of Agricultural Science
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    • v.46 no.1
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    • pp.67-78
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    • 2019
  • The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

Development of a Framework for Improvement of Sensor Data Quality from Weather Buoys (해양기상부표의 센서 데이터 품질 향상을 위한 프레임워크 개발)

  • Ju-Yong Lee;Jae-Young Lee;Jiwoo Lee;Sangmun Shin;Jun-hyuk Jang;Jun-Hee Han
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.3
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    • pp.186-197
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    • 2023
  • In this study, we focus on the improvement of data quality transmitted from a weather buoy that guides a route of ships. The buoy has an Internet-of-Thing (IoT) including sensors to collect meteorological data and the buoy's status, and it also has a wireless communication device to send them to the central database in a ground control center and ships nearby. The time interval of data collected by the sensor is irregular, and fault data is often detected. Therefore, this study provides a framework to improve data quality using machine learning models. The normal data pattern is trained by machine learning models, and the trained models detect the fault data from the collected data set of the sensor and adjust them. For determining fault data, interquartile range (IQR) removes the value outside the outlier, and an NGBoost algorithm removes the data above the upper bound and below the lower bound. The removed data is interpolated using NGBoost or long-short term memory (LSTM) algorithm. The performance of the suggested process is evaluated by actual weather buoy data from Korea to improve the quality of 'AIR_TEMPERATURE' data by using other data from the same buoy. The performance of our proposed framework has been validated through computational experiments based on real-world data, confirming its suitability for practical applications in real-world scenarios.

Effects of hygro-thermal environment on dynamic responses of variable thickness functionally graded porous microplates

  • Quoc-Hoa Pham;Phu-Cuong Nguyen;Van-Ke Tran
    • Steel and Composite Structures
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    • v.50 no.5
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    • pp.563-581
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    • 2024
  • This paper presents a novel finite element model for the free vibration analysis of variable-thickness functionally graded porous (FGP) microplates resting on Pasternak's medium in the hygro-thermal environment. The governing equations are established according to refined higher-order shear deformation plate theory (RPT) in construction with the modified couple stress theory. For the first time, three-node triangular elements with twelve degrees of freedom for each node are developed based on Hermitian interpolation functions to describe the in-plane displacements and transverse displacements of microplates. Two laws of variable thickness of FGP microplates, including the linear law and the nonlinear law in the x-direction are investigated. Effects of thermal and moisture changes on microplates are assumed to vary continuously from the bottom surface to the top surface and only cause tension loads in the plane, which does not change the material's mechanical properties. The numerical results of this work are compared with those of published data to verify the accuracy and reliability of the proposed method. In addition, the parameter study is conducted to explore the effects of geometrical and material properties such as the changing law of the thickness, length-scale parameter, and the parameters of the porosity, temperature, and humidity on the free vibration response of variable thickness FGP microplates. These results can be applied to design of microelectromechanical structures in practice.

Plant Hardiness Zone Mapping Based on a Combined Risk Analysis Using Dormancy Depth Index and Low Temperature Extremes - A Case Study with "Campbell Early" Grapevine - (최저기온과 휴면심도 기반의 동해위험도를 활용한 'Campbell Early' 포도의 내동성 지도 제작)

  • Chung, U-Ran;Kim, Soo-Ock;Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.10 no.4
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    • pp.121-131
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    • 2008
  • This study was conducted to delineate temporal and spatial patterns of potential risk of cold injury by combining the short-term cold hardiness of Campbell Early grapevine and the IPCC projected climate winter season minimum temperature at a landscape scale. Gridded data sets of daily maximum and minimum temperature with a 270m cell spacing ("High Definition Digital Temperature Map", HD-DTM) were prepared for the current climatological normal year (1971-2000) based on observations at the 56 Korea Meteorological Administration (KMA) stations using a geospatial interpolation scheme for correcting land surface effects (e.g., land use, topography, and elevation). The same procedure was applied to the official temperature projection dataset covering South Korea (under the auspices of the IPCC-SRES A2 and A1B scenarios) for 2071-2100. The dormancy depth model was run with the gridded datasets to estimate the geographical pattern of any changes in the short-term cold hardiness of Campbell Early across South Korea for the current and future normal years (1971-2000 and 2071-2100). We combined this result with the projected mean annual minimum temperature for each period to obtain the potential risk of cold injury. Results showed that both the land areas with the normal cold-hardiness (-150 and below for dormancy depth) and those with the sub-threshold temperature for freezing damage ($-15^{\circ}C$ and below) will decrease in 2071-2100, reducing the freezing risk. Although more land area will encounter less risk in the future, the land area with higher risk (>70%) will expand from 14% at the current normal year to 23 (A1B) ${\sim}5%$ (A2) in the future. Our method can be applied to other deciduous fruit trees for delineating geographical shift of cold-hardiness zone under the projected climate change in the future, thereby providing valuable information for adaptation strategy in fruit industry.