• Journal of Korean Society on Water Environment
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• v.29 no.2
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• pp.247-258
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• 2013

A grid-based configuration of Land Surface Models (LSMs) coupled with a climate model can be advantageous in impact assessment of climate change for a large scale area. We assessed the applicability of Common Land Model (CoLM) to runoff and land surface temperature (LST) simulations at the domain that encompasses the Nakdong river basin. To establish a high resolution model configuration of a $1km{\times}1km$ grid size, both surface boundary condition and atmospheric inputs from the observed weather data in 2009 were adjusted to the same resolution. The Leaf Area Index (LAI) was collected from MODerate esolution Imaging Spectroradiometer (MODIS) and the downward short wave flux was produced by a nonstationary multi-site weather state model. Compared with the observed runoffs at the stations on Nakdong river, simulated runoffs properly responded to rainfall. The spatial features and the seasonal variations of the domain fairly well were captured in the simulated LSTs as well. The monthly and seasonal trend of LST were described well compared to the observations, however, the monthly averaged simulated LST exceeded the observed up to $2^{\circ}C$ at the 24 stations. From the results of our study, it is shown that high resolution LSMs can be used to evaluate not only quantity but also quality of water resources as it can capture the geographical features of the area of interest and its rainfall-runoff response.

• Journal of Korean Society for Quality Management
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• v.8 no.1
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• pp.3-7
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• 1980

In many industrial processes, there are more than two responses (i.e., yield, percent impurity, etc.) of interest, and it is desirable to determine the optimal levels of the factors (i.e., temperature, pressure, etc.) that influence the responses. Suppose the response relationships are assumed to be approximated by second-order polynomial regression models. The problems considered in this paper is, first, to propose how to select polynomial terms to fit the multivariate regression surfaces for a given set of data, and, second, to propose how to analyze the data to obtain an optimal operating condition for the factors. The proposed techniques were applied for empirical process optimization in a tire company in Korea. This case is presented as an illustration.

• Journal of Korean Society on Water Environment
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• v.36 no.1
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• pp.14-28
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• 2020

Future climate change may affect the hydro-thermal and biogeochemical characteristics of dam reservoirs, the most important water resources in Korea. Thus, scientific projection of the impact of climate change on the reservoir environment, factoring uncertainties, is crucial for sustainable water use. The purpose of this study was to predict the future water temperature and stratification structure of the Soyanggang Reservoir in response to a total of 42 scenarios, combining two climate scenarios, seven GCM models, one surface runoff model, and three wind scenarios of hydrodynamic model, and to quantify the uncertainty of each modeling step and scenario. Although there are differences depending on the scenarios, the annual reservoir water temperature tended to rise steadily. In the RCP 4.5 and 8.5 scenarios, the upper water temperature is expected to rise by 0.029 ℃ (±0.012)/year and 0.048 ℃ (±0.014)/year, respectively. These rise rates are correspond to 88.1 % and 85.7 % of the air temperature rise rate. Meanwhile, the lower water temperature is expected to rise by 0.016 ℃ (±0.009)/year and 0.027 ℃ (±0.010)/year, respectively, which is approximately 48.6 % and 46.3 % of the air temperature rise rate. Additionally, as the water temperatures rises, the stratification strength of the reservoir is expected to be stronger, and the number of days when the temperature difference between the upper and lower layers exceeds 5 ℃ increases in the future. As a result of uncertainty quantification, the uncertainty of the GCM models showed the highest contribution with 55.8 %, followed by 30.8 % RCP scenario, and 12.8 % W2 model.

• Design & Manufacturing
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• v.16 no.1
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• pp.62-69
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• 2022

In the present study, the injection molding optimization of a large thick LH type elastic frames for the reduction of warpage was performed. Two kinds of fine and coarse finite element models were prepared to investigate the efficiency of analysis time and quality on simulation results. In order to derive injection molding conditions that can minimize distortion of parts, it was investigated that the effects of mold temperature, resin temperature, injection time, hold pressure switching time, holding pressure and the hold time on deformation characteristics using the design of experiments. The main influential factors on the warpage were found from the optimization simulation and the geometry data of the warpage result was converted into an initial model for injection simulation. It was shown that a coarse model with good mesh quality could be adapted for mold design since the total analysis time using the proposed model was reduced to 1/10. The suggested inversed warpage model produced the best minimized result of warpage.

• Journal of the Korean Society of Safety
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• v.16 no.2
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• pp.121-129
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• 2001

This paper demonstrates the development of optical temperature sensor based on the etched planar waveguide Bragg grating. Topics include design and fabrication of the etched planar waveguide Bragg grating, investigation of the grating reflection characteristics, and temperature measurement capabilities. The typical bandwidth and reflectivity of the surface etched grating has been ~0.2nm and ~7%, respectively, at a wavelength of ～1552nm. The temperature-induced wavelength change of the optical sensor is found to be slightly non-linear over ～20$0^{\circ}C$ temperature range. Theoretical models for the grating response of the sensor based on waveguide and plate deformation theories agree with experiments to within acceptable tolerance.

• Journal of the Korean Society of Food Science and Nutrition
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• v.26 no.5
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• pp.831-837
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• 1997

Response surface methodology(RSM) was applied in roasting processes of Polygonatum odoratum roots in order to monitor Hunter color parameters and to optimize organoleptic properties of the tea. In roasting processing based on the central composite design with variations in roasting temperature (110~19$0^{\circ}C$) and roasting time(15~75min), coefficients of determinations($R^{2}$) of the models were above 0.9827(p<0.01) in Hunter color parameters and above 0.7748 in organoleptic properties. Hunter color L and $\Delta$E values of the powdered samples decreased with the roasting processes, whereas Hunter color a and b values increased up to around 59 min at 136$^{\circ}C$ and thereafter showed a decreased tendency. Organoleptic qualities on color, taste and aroma of Polygonatum odoratum tea were improved along with roasting processes, thereby estimating the optimum roasting conditions by RSM for the maximized qualities of organoleptic properties as a range from 127$^{\circ}C$ to 135$^{\circ}C$ and from 60min to 66 min. Hunter color a value(redness) was found to generate a similar response surface to that of organoleptic properties, showing the possibility of quality index in roasting processes of Polygonatum odoratum roots.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.312-319
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• 2013

Our understanding of the sensitivities of crop responses to changes in carbon dioxide, temperature, and water is limited, which makes it difficult to fully utilize crop models in assessing the impact of climate change on future agricultural production. Genetic coefficients of CERES-Barley model for major domestic cultivars in South Korea (Olbori at Suwon, Albori at Milyang, Saessalbori at Iksan, and Samdobori at Jinju) were estimated from the observed data for daily weather and field trials for more than 10 years by using GenCalc in DSSAT. Data from 1997-2002 annual crop status report (Rural Development Administration, RDA) were used to validate the crop coefficients. The sitecalibrated CERES-Barley model was used to perform crop growth simulation with the 99 treatments of step change combinations in temperature, precipitation and carbon dioxide concentration with respect to the baseline climate (1981-2010) at four sites. The upper boundary corresponds to the 2071-2100 climate outlook from the RCP 8.5 scenario. The response surface of grain yield showed a distinct pattern of model behavior under the combined change in environmental variables. The simulated grain yield was most sensitive to $CO_2$ concentration, least sensitive to precipitation, and showing a variable response to temperature depending on cultivar. The emulated impacts of response surfaces are expected to facilitate assessment of projected climate impacts on a given cultivar in South Korea.

• Structural Engineering and Mechanics
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• v.88 no.6
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• pp.521-533
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• 2023

In the present study, the finite volume method is applied for the thermal performance prediction of the natural ventilation system using vertical solar chimney whereas, design parameters are optimized through the response surface methodology (RSM). The computational simulations are performed for various parameters of the solar chimney such as absorber temperature (40≤T_abs≤70℃), inlet temperature (20≤T₀≤30℃), inlet height of (0.1≤h≤0.2 m) and chimney width (0.1≤d≤0.2 m). Analysis of variance (ANOVA) was carried out to identify the design parameters that influence the average Nusselt number (Nu) and mass flow rate (ṁ). Then, quadratic polynomial regression models were developed to predict of all the response parameters. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are Nu=25.67 and ṁ=24.68 kg/h·m, corresponding to design parameters h=0.18 m, d=0.2 m, T_abs=46.81℃ and T₀=20℃. The optimal ventilation flow rate is enhanced by about 96.65% compared to the minimum ventilation rate, while solar energy consumption is reduced by 49.54% compared to the maximum ventilation rate.

• Journal of Ginseng Research
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• v.23 no.3 s.55
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• pp.164-171
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• 1999

Microwave-assisted extraction, which is known to rapidly extract target compounds from natural products, was monitored by response surface methodology (RSM) while extracting ginsenosides by using microwave extraction system (MES) equipped with closed vessels, and was confirmed on its extraction efficiency. On the whole, coefficients of determinations $(R^2)$ of the models on ginsenoside contents of extracts with various extraction conditions were above 0.83 (p<0.1). $Ginsenoside-Rb_2,\;-Rc,\;-Re\;and\;-Rg_1$ were maximized in $140^{\circ}C$ of extraction temperature and $50\~75\%$ range of ethanol concentration. Unknown compound peak on HPLC chromatogram observed at extraction temperature over $120^{\circ}C$, increased at the extraction temperature of $150^{\circ}C$. The extraction temperature of $ginsenoside-Rb_2$ and -Re increased from $129^{\circ}C\;to\;147^{\circ}C$ with including unknown compound, and $R^2$ of the models on ginsenoside contents of extracts increased with including unknown compound into ginsenoside $Rb_2$ and Re. Contents of unknown compound were minimized in $67.33\%$ of ethanol concentration, $99.34^{\circ}C$ of extraction temperature and 3.65 min of extraction time. Ginsenoside contents extracted by microwave system for 8 min showed a similar tendency to those of the current extraction method for 40 hrs.

• Journal of Korean Society on Water Environment
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• v.35 no.3
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• pp.234-247
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• 2019

In a deep lake and reservoir, thermal stratification is of great importance for characteristics of hydrodynamic mixing of the waterbody, and thereby influencesvertical distribution of dissolved oxygen, substances, nutrients, and the phytoplankton community. The purpose of this study, was to project the effect of a future climate change scenario on water temperature, stratification strength, and thermal stability in the Soyanggang Reservoir in the Han River basin of South Korea, using a suite of mathematical models; SWAT, HEC-ResSim, and CE-QUAL-W2(W2). W2 was calibrated with historical data observed 2005-2015. Using climate data generated by HadGEM2-AO with the RCP 4.5 scenario, SWAT predicted daily reservoir inflow 2016-2070, and HEC-ResSim simulated changes in reservoir discharge and water level, based on inflow and reservoir operation rules. Then, W2 was applied, to predict long-term continuous changes of water temperature, in the reservoir. As a result, the upper layer (5 m below water surface) and lower layer (5 m above bottom) water temperatures, were projected to rise $0.0191^{\circ}C/year$(p<0.05) and $0.008^{\circ}C/year$(p<0.05), respectively, in response to projected atmospheric temperature rise rate of $0.0279^{\circ}C/year$(p<0.05). Additionally, with increase of future temperature, stratification strength of the reservoir is projected to be stronger, and the number of the days when temperature difference of the upper layer and the lower layer becomes greater than $5^{\circ}C$, also increase. Increase of water temperature on the surface of the reservoir, affected seasonal growth rate of the algae community. In particular, the growth rate of cyanobacteria increased in spring, and early summer.