• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.6
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• pp.505-513
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• 2005

We measured the time-dependent concentration of VOCs emitted from Ondol floor, furniture, and the wall made of various building materials. After obtaining results from the previous measurement, we developed the estimation equations of the concentration decay, and obtained the estimated graphs for the concentration decay under different air change rates and loading factor conditions by using the estimated equations. We conducted our tests by applying our measurements to real residences for 110 days in the case of furniture and for 40 days in the case of the floor. We also conducted experiments in the cases of various wall materials for 7 days which totaled 10 times. We used the GC/FID for experiments for real residences accord-ing to the specified procedures of the NIOSH 1501, and carried out experiments for wall materials according to the specified procedures of the ASTM 5116-97. When conducting experiments for wall materials, we set the temperature and relative humidity at $23^{\circ}C$ and $50\%$, respectively. We also set the air change rate and loading factor at 0.7/h and $1.617 m^2/m^3$, respectively. Our results showed that it is possible to predict proplrly the time-dependent concentration decay of VOCs by using logarithmic functions in both cases of experiments for real residences and for wall materials. Furthermore, we found that the concentration decay rate of VOCs increased rapidly as the air exchange rate increased while the concentration decay rate decreased as the loading factor increased.

• Korean Journal of Soil Science and Fertilizer
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• v.21 no.1
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• pp.11-14
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• 1988

Field study was conducted to evaluate the relationship between daytime net radiation (Drn) and global solar radiation (Rs) and to develop the empirical equation predicting daytime net radiation above corn canopy from observations of Rs and Ta (mean daily air temperature). The relationship between Drn and Rs under the cloudless day was Drn = 0.6659Rs and that under the cloudy (> 35% of possible sunshine) Drn = 0.729Rs. Thus, Drn/Rs Ratio under cloudless day was found to be lower than that under the cloudy day. Rs and Ta were used in the radiation balance equation to estimate Drn and the empirical model could be expressed as $Drn=[0.9Rs-(352-227{\times}10^{-10}{\times}Ta^4)]$ [1.11Rs/Rso - 0.05].

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.61-75
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• 2021

This study aims to assess the changes in crop water requirement of paddy and upland according to future climate and land use changes scenarios. Changes in the spatiotemporal distribution of temperature and precipitation are factors that lower the stability of agricultural water supply, and predicting the changes in crop water requirement in consideration of climate change can prevent the waste of limited water resources. Meanwhile, due to the recent changes in the agricultural product consumption structure, the area of paddy and upland has been changing, and it is necessary to consider future land use changes in establishing an appropriate water use plan. Climate change scenarios were derived from the four GCMs of the CMIP6, and climate data were extracted under two future scenarios, namely SSP1-2.6 and SSP5-8.5. Future land use changes were predicted using the FLUS (Future Land Use Simulation) model. Crop water requirement in paddy was calculated as the sum of evapotranspiration and infiltration based on the water balance in a paddy field, and crop water requirement in upland was estimated as the evapotranspiration value by applying Penman-Monteith method. It was found that the crop water requirement for both paddy and upland increased as we go to the far future, and the degree of increase and variability by time showed different results for each GCM. The results derived from this study can be used as basic data to develop sustainable water resource management techniques considering future watershed environmental changes.

• Ocean and Polar Research
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• v.43 no.2
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• pp.89-98
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• 2021

The seagrass habitats are a highly productive marine ecosystem which provides nursery ground and shelter for many fish and invertebrate species. Pholis nebulosa (Temminck & Schlegel, 1845) is one of the most abundant seagrass fishes in the coastal waters of Korea. The estimation of fish production is key for devising conservation measures and ensuring fish resources sustainability. A total 894 P. nebulosa ranging from 3.83 to 26.5 cm total length (TL) were collected monthly in 2006 with a small beam trawl in a seagrass bed of southern Korea. Growth parameters of P. nebulosa were estimated using the von Bertalanffy growth model, and production was estimated using a general equation which relates daily fish production to ash-free dry weight (AFDW), biomass, and water temperature. The von Bertalanffy's growth equation was estimated as: L_t = 28.3823(1-e^{-0.7835(t+0.9864)}). The densities, biomass, daily, annual production, and P/B ratio were 0.069±0.061/m^-2, 1.022±0.621 g/m², 0.005±0.004 g AFDW/m²/day, 1.676 g AFDW/m²/yr, and 1.641, respectively. Monthly variation in production of P. nebulosa peaked during March and April 2006 (0.0139 and 0.0111 g AFDW/m²/day), whereas the lowest value of 0.0005 g AFDW/m²/day was in December. Monthly change in production of P. nebulosa was positively correlated with biomass and condition factor. Our results will contribute to the conservation of seagrass ecosystems, which are still undisturbed in the study area.

• Atmosphere
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• v.29 no.3
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• pp.269-282
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• 2019

While it is important to obtain the accurate information on snowfall data due to the increase in damage caused by the heavy snowfall in the winter season, it is not easy to observe the snowfall quantitatively. Recently, snow measurements using a weighing precipitation gauge have been carried out, but there is a problem that high snowfall intensity results in low accuracy. Also, the observed snowfall data are sensitive depending on wind speed, temperature, and humidity. In this study, a new process of quality control for snow water equivalent (SWE) data of the weighing precipitation gauge were proposed to cover the low accuracy of snow data and maximize the data utilization. Snowfall data (SWE) observed by Pluvio, Parsivel, snow-depth meter using laser or ultrasonic, and rainfall gauge in Cloud Physics Observation Site (CPOS) were compared and analyzed. Applying the QC algorithm including the use of number of hydrometeor particles as reference, the increased SWE per the unit time was determined and the data noise was removed and marked by flag. The SWE data converted by the number concentration of hydrometeor particles are tested as a method to restore the QC-removed data, and show good agreement with those of the weighing precipitation gauge, though requiring more case studies. The three events data for heavy snowfall disaster in Pyeongchang area was analyzed. The SWE data with improved quality was showed a good correlation with the eye-measured data ($R^2$ > 0.73).

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.105-112
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• 2019

Due to abnormal high temperature, electric power demand has exceeded the backup power reserved for emergency case, hence, resulting in a major power outage. In today's overcrowded cities, the unexpected disruption in energy supply and demand is a major threat to the enormous economic damage and urban malfunctions. Existing methods for estimating the demand of the emergency power source do not lend themselves to predict the actual demand in the spatial dimension of the city. In addition, the reserve power is arbitrarily distributed in the case of emergency. This paper presents a method that predicts the emergency power demand using the spatial distribution of emergency power demand by applying the daily energy consumption intensity and emergency power demand according to urban spatial information and building use.

• Corrosion Science and Technology
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• v.18 no.2
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• pp.61-71
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• 2019

Flow-Accelerated Corrosion (FAC) is a phenomenon in which a protective coating on a metal surface is dissolved by a flow of fluid in a metal pipe, leading to continuous wall-thinning. Recently, many countries have developed computer codes to manage FAC in power plants, and the FAC prediction model in these computer codes plays an important role in predictive performance. Herein, the FAC prediction model was developed by applying a machine learning method and the conventional nonlinear regression method. The random forest, a widely used machine learning technique in predictive modeling led to easy calculation of FAC tendency for five input variables: flow rate, temperature, pH, Cr content, and dissolved oxygen concentration. However, the model showed significant errors in some input conditions, and it was difficult to obtain proper regression results without using additional data points. In contrast, nonlinear regression analysis predicted robust estimation even with relatively insufficient data by assuming an empirical equation and the model showed better predictive power when the interaction between DO and pH was considered. The comparative analysis of this study is believed to provide important insights for developing a more sophisticated FAC prediction model.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.5
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• pp.787-797
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• 2021

Yellowtail Seriola quinqueradiata tagged with a Pop-up Satellite Archival Tag (PSAT) was released off the coast of near the Moseulpo, Jeju Island and the ecological data during about 40 days was obtained. However, it is difficult to determine the spatial location of underwater ecological data. To improve the accuracy of estimating the Yellowtail migration route using temperature, suitable background field of the oceanic environment data was evaluated and used for input data. After developing of the tracking algorithm for migration route estimation, three experiment cases were estimated with ecological data among the surface layer, the mixed layer, and the whole water column. All tracking experiments move from western to eastern Jeju Island. Additionally, tracking experiment using 3D ocean numerical model reveal that it is possible to estimate the migration route using the fish ecological data of the entire water column. Therefore, using a large number of ecological data and a high-accuracy ocean numerical model to estimate the migration route seems to be a way to increase the accuracy of the tracking experiment. Moreover, the tracking algorithm of this study can be applied to small pelagic fishery using small archival electronic tags to track the migration route.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.233-238
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• 2020

Process-based model (PBM), based on the interactions between endogenous physiological processes and many environmental factors, can be a powerful tool for estimating crop growth and productivity. Carbon acquisition and biomass accumulation are the main components in PBM, so it has become important to understand and integrate gas exchange process in crop model. This study aimed to assess the applicability of FvCB model (a leaf model of C3 photosynthesis proposed by Farquhar, von C aemmerer, and Berry (1980)) in onion (Allium cepa L.). For parameterization, two early-maturing onion cultivars, 'Singsingball' and 'Thunderball', grown in a temperature gradient plastic film house, were used in measuring leaf net CO2 assimilation rate (A), and then, parameter estimation was carried out for four parameters including Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), TPU (rate of triose phosphate utilization), and Rd (Dark respiration rate). The gas-exchange model calibrated in this research is expected to be able to explain the photosynthetic responses of onion under various environmental conditions (R2=0.95***).

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.1-13
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• 2022

In Korea, attention is being paid to the use of renewable energy in the livestock industry, and Ground Source Heat Pump (GSHP), which is advantageous for temperature control, is considered as one of the ways to reduce the use of fossil fuels. But GSHP is expensive to install, which proper capacity calculation is required. GSHP capacity is related to its maximum energy load. Energy loads are affected by climate characteristics and time, so dynamic analysis is required. In this study, the optimal capacity of GSHP was calculated by calculating the heating and cooling load of pig farms using BES (Building Energy Simulation) and economic analysis was performed. After designing the inside of the pig house using TRNSYS, one of the commercial programs of the BES technique, the energy load was calculated based on meteorological data. Through the calculated energy load, three heating devices and GSHP used in pig farms were analyzed for economic feasibility. As a result, GSHP's total cost of ownership was the cheapest, but the installation cost was the highest. In order to reduce the initial cost of GSHP, the capacity of GSHP was divided, and a scenario was created in which some of it was used as an auxiliary heating device, and economic analysis was conducted. In this study, a method to calculate the proper capacity of GSHP through dynamic energy analysis was proposed, and it can be used as data necessary to expand the spread of GSHP.