• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.485-488
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• 2007

Riverbank filtration is a kind of artificial aquifer recharge for the fresh water supply. By construction of several production wells penetrating the riverbank, surface water withdrawn from the river would pass riverbed. This extracted water is well known to be cooler than surface water in summer and warmer than surface water in winter, showing more constant water temperature. This characteristic of extracted water is applied to geothermal energy utilization. Prediction of the annual temperature variation of filtrated water is the major concern in this study. In Daesan-myeon, Changwon-si, Gyeongsangnam-do, South Korea, riverbank filtration facility has been on its operation for municipal water supply and thermal energy utilization since 2006. Appropriate hydraulic and thermal properties were estimated for flow and heat transfer modeling with given pumping rate and location. With the calibrated material properties and boundary conditions, we numerically reproduced measured head and temperature variation with acceptable error range. In the numerical simulation, the change of saturation ratio and river stage caused by rainfall was calculated and the resulting variation of thermal capacity and thermal conductivity was considered. Simulated temperature profiles can be used to assess the possible efficiency of geothermal energy utilization using riverbank filtration facility. Influence of pumping rate, pumping location on the extracted water temperature will be studied.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.686-693
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• 2014

This study presents a model that enables to predict road surface temperature using neural network theory. Historical road surface temperature data were collected from Road Weather Information System. They used for the calibration of the model. The neural network was designed to predict surface temperature after 1-hour, 2-hour, and 3-hour from now. The developed model was performed on Cheongwon-Sangju highway to test. As a result, the standard deviation of the difference of the predicted and observed was $1.27^{\circ}C$, $0.55^{\circ}C$ and $1.43^{\circ}C$, respectively. Also, comparing the predicted surface temperature and the actual data, R2 was found to be 0.985, 0.923, and 0.903, respectively. It can be concluded that the explanatory power of the model seems to be high.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.285-289
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• 2017

Laser-induced breakdown spesctroscopy (LIBS) is a technique that complements the disadvantages of conventional laser-based combustion diagnosis techniques such as weak signal strength, complex equipment configuration, and low accuracy. In this study, basic research was carried out to measure the combustion gas temperature of scramjet engines using LIBS. Spray flames were generated from Jet A-1 fuel used in scramjet engines and gas temperatures were measured at the top of the flames with a calibrated thermocouple. The LIBS signals were acquired at the same points as the temperature measurement positions of the thermocouple. The LIBS spectra were analyzed to obtained a calibration curve between the LIBS signal and the reference temperature measured at the thermocouple. Therefore, it was confirmed that the combustion gas temperature can be measured in-situ using LIBS.

• Ocean and Polar Research
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• v.36 no.1
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• pp.39-47
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• 2014

The black scraper Thamnaconus modestus was a commercially important fish species in the 1980s, but suddenly its commercial significance decreased in the 1990s mainly due to continuous overfishing. Recently, in order to reverse the depleted stocks of the black scraper and help the species recover, seed production technology has emerged. This has led to the farming of the black scraper in several parts of the southern coast of Korea. Since detailed research on its metabolism in relation to water temperature has been scanty, this was the investigative focus of the present study. The standard metabolism rates of the black scraper (9-10 months old, total length=$22.6{\pm}0.8cm$, wet weight=$140.3{\pm}13.9g$) were measured at seven different water temperature settings (12, 15, 17, 20, 23, 26, $28^{\circ}C$) to understand the relationship between metabolism and water temperature. Relationships between water temperature (WT) and oxygen consumption rate (OCR) were obtained as SOCR (weight-specific oxygen consumption rate) = 0.0117WT - 0.0135 ($r^2=0.9351$) and IOCR (oxygen consumption rate per individual) = 1.8160WT - 5.4007 ($r^2$ = 9428). The $Q_{10}$ (temperature sensitivity), an indicator of the sensitivity of biological function to temperature, was analyzed. In our experiment, when the water temperature increased, the $Q_{10}$ value decreased. The $Q_{10}$ value was 6.27 in waters where the temperature ranged from $12-15^{\circ}C$ and this was much higher than the values obtained in waters where temperatures ranged between (1) $15-23^{\circ}C$ and (2) $23-28^{\circ}C$. Consequently, it was shown that the black scraper is a warm water species and inhabiting waters in the temperature range from $15-28^{\circ}C$ is deemed appropriate.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.61-70
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• 2011

This study developed a permanent deformation model for asphalt concrete based on shear properties. Repeated load triaxial compression (RLTC), triaxial compressive strength, and indirect tension strength tests were performed for the three types of asphalt mixtures at various loading and temperature conditions to correlate shear properties of asphalt mixtures to rutting performance. For the given mixtures, as testing temperature increased, cohesion decreased, but friction angle was insensitive to temperature at $40^{\circ}C$ or higher. It was observed that deviatoric stress, confining pressure, temperature, and load frequency affected the permanent deformation of asphalt mixtures significantly. The permanent deformation model based on shear stress to strength ratio and loading time was developed using the laboratory test results and calibrated using accelerated pavement test data. The proposed model was able to predict the permanent deformation of the asphalt mixtures in a wide range of loading and temperature conditions with constant model coefficients.

• Smart Structures and Systems
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• v.15 no.3
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• pp.665-682
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• 2015

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.90-98
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• 2022

The output of an infrared (IR) sensor mounted on an EO/IR payload is known to change during a mission period in an orbital environment. As it is required to calibrate the output of the IR sensor periodically to obtain high-quality images, an on-board black body system is mounted on the payload. All systems operating in the space environment require performance tests on ground to verify the target performance in the orbital environment. Therefore, it is also required to test the black body system to verify the performance of the surface temperature uniformity and the estimated representative temperature error within the target temperature range in the operating environment. In this study, calibration of the estimated representative temperature error and verification of the thermal performance of the black body system were conducted by performed a performance test in the thermal vacuum chamber applying deep space radiation cooling effect of an orbital environment.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.251-262
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• 2010

In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.7 no.1
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• pp.151-162
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• 1997

The suitability of pivalic acid was confirmed as a secondary temperature standard material. Triple-point cells of pivalic acid were obtained by using combined process of vacuum distillation with zone refining. A detailed description of the purification process was given. The melting curves were used as criteria for determination of purities of pivalic acid. Triple points of these cells with purity of 99.9997% were measured to be $35.956\pm 0.003^{\circ}C$ by using the melting plateau curves. Thus the triple point cells of pivalic acid appear to be able to use for the calibration of thermistor thermometers with moderate precision.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.589-593
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• 2013

Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.