• Ocean Science Journal
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• v.40 no.3
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• pp.167-176
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• 2005

A time-series sediment trap was deployed at 1,034 m water depth in the eastern Bransfield Strait for a complete year from December 25, 1998 to December 24, 1999. About 99% of total mass flux was trapped during an austral summer, showing distinct seasonal variation. Biogenic particles (biogenic opal, particulate organic carbon, and calcium carbonate) account for about two thirds of annual total mass flux $(49.2\;g\;m^{-2})$, among which biogenic opal flux is the most dominant (42% of the total flux). A positive relationship (except January) between biogenic opal and total organic carbon fluxes suggests that these two variables were coupled, due to the surface-water production (mainly diatoms). The relatively low $\delta^{13}C$ values of settling particles result from effects on C-fixation processes at low temperature and the high $CO_2$ availability to phytoplankton. The correspondingly low $\delta^{l5}N$ values are due to intense and steady input of nitrates into surface waters, reflecting an unlikely nitrate isotope fractionation by degree of surface-water production. The $\delta^{l5}N$ and $\delta^{l3}C$ values of sinking particles increased from the beginning to the end of a presumed phytoplankton bloom, except for anomalous $\delta^{l5}N$ values. Krill and the zooplankton fecal pellets, the most important carriers of sinking particles, may have contributed gradually to the increasing $\delta^{l3}C$ values towards the unproductive period through the biomodification of the $\delta^{l3}C$ values in the food web, respiring preferentially and selectively $^{12}C$ atoms. Correspondingly, the increasing $\delta^{l5}N$ values in the intermediate-water trap are likely associated with a switch in source from diatom aggregates to some remains of zooplankton, because organic matter dominated by diatom may be more liable and prone to remineralization, leading to greater isotopic alteration. In particular, the tendency for abnormally high $\delta^{l5}N$ values in February seems to be enigmatic. A specific species dominancy during the production may be suggested as a possible and speculative reason.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.478-478
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• 2012

Recently, there are many researches in order to increase the deposition rate (D/R) and improve film uniformity and quality in the deposition of microcrystalline silicon thin film. These two factors are the most important issues in the fabrication of the thin film solar cell, and for the purpose of that, several process conditions, including the large area electrode (more than 1.1 X 1.3 (m2)), higher pressure (1 ~ 10 (Torr)), and very high frequency regime (VHF, 40 ~ 100 (MHz)), have been needed. But, in the case of large-area capacitively coupled discharges (CCP) driven at frequencies higher than the usual RF (13.56 (MHz)) frequency, the standing wave and skin effects should be the critical problems for obtaining the good plasma uniformity, and the ion damage on the thin film layer due to the high voltage between the substrate and the bulk plasma might cause the defects which degrade the film quality. In this study, we will propose the new concept of the large-area multi-electrode (a new multi-electrode concept for the large-area plasma source), which consists of a series of electrodes and grounds arranged by turns. The experimental results with this new electrode showed the processing performances of high D/R (1 ~ 2 (nm/sec)), controllable crystallinity (~70% and controllable), and good uniformity (less than 10%) at the conditions of the relatively high frequency of 40 MHz in the large-area electrode of 280 X 540 mm2. And, we also observed the SEM images of the deposited thin film at the conditions of peeling, normal microcrystalline, and powder formation, and discussed the mechanisms of the crystal formation and voids generation in the film in order to try the enhancement of the film quality compared to the cases of normal VHF capacitive discharges. Also, we will discuss the relation between the processing parameters (including gap length between electrode and substrate, operating pressure) and the processing results (D/R and crystallinity) with the process condition map for ${\mu}c$-Si:H formation at a fixed input power and gas flow rate. Finally, we will discuss the potential of the multi-electrode of the 3.5G-class large-area plasma processing (650 X 550 (mm2) to the possibility of the expansion of the new electrode concept to 8G class large-area plasma processing and the additional issues in order to improve the process efficiency.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.6
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• pp.113-125
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• 2017

In spite of bulk literature about the tuning of TMD, the effectiveness of TMD in reducing the seismic response of engineering structures is still in a row. This paper deals with the optimum tuning parameters of a passive TMD and simulated on MATLAB with a ten-story numerical shear building. A weighted multi-objective optimization method based on computer experiment consisting of coupled with central composite design(CCD) central composite design and response surface methodology(RSM) was applied to find out the optimum tuning parameters of TMD. After the optimization, the so-conceived TMD turns out to be optimal with respect to the specific seismic event, hence allowing for an optimum reduction in seismic response. The method was employed on above structure by assuming first the El Centro seismic input as a sort of benchmark excitation, and then additional recent strong-motion earthquakes. It is found that the RSM based weighted multi-objective optimized damper improves frequency responses and root mean square displacements of the structure without TMD by 31.6% and 82.3% under El Centro earthquake, respectively, and has an equal or higher performance than the conventionally designed dampers with respect to frequency responses and root mean square displacements and when applied to earthquakes.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.277-284
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• 2020

To increase the utilization of the intelligent methodology of smart farm management, estimation modeling techniques are required to assess prior examination of crops and environment changes in realtime. A mandatory environmental factor such as CO₂ is challenging to establish a reliable estimation model in time domain accounted for indoor agricultural facilities where various correlated variables are highly coupled. Thus, this study was conducted to develop an artificial neural network for reducing time complexity by using environmental information distributed in adjacent areas from a time perspective as input and output variables as CO₂. The environmental factors in the smart farm were continuously measured using measuring devices that integrated sensors through experiments. Modeling 1 predicted by the mean data of the experiment period and modeling 2 predicted by the day-to-day data were constructed to predict the correlation of CO₂. Modeling 2 predicted by the previous day's data learning performed better than Modeling 1 predicted by the 60-day average value. Until 30 days, most of them showed a coefficient of determination between 0.70 and 0.88, and Model 2 was about 0.05 higher. However, after 30 days, the modeling coefficients of both models showed low values below 0.50. According to the modeling approach, comparing and analyzing the values of the determinants showed that data from adjacent time zones were relatively high performance at points requiring prediction rather than a fixed neural network model.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.96-108
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• 2011

Going abreast of high public concerns on the environment, the need of environmental modeling has been increased to assess the impact of space exploitation of environment. GIS offers potential solutions to the many problems encountered during water-quality modeling. But there are also many problems associated with the modeling. The preparation of necessary parameters for the modeling can be complicated. Also, the results from one model can be different from each other even the same area is analyzed. This paper aims to develop the data processing system to couple the Qual2E and HyGIS in which Qual2E input and output data files can be created, modified and processed using HyGIS and assess the performance of the system. A structural analysis and standardization of modeling are conducted to identify data flow and processing of Qual2E. Algorithms of the defined processors are designed and developed as component modules. The data model of HyGIS-Qual2E is designed, and GUI(Graphical User Interface) is developed using Visual Basic 6.0 and GDK.

• Economic and Environmental Geology
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• v.50 no.3
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• pp.239-250
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• 2017

Physically based landslide susceptibility analysis has been recognized as an effective analysis method because it can consider the mechanism of landslide occurrence. The physically based analysis used the slope geometry and geotechnical properties of slope materials as input. However, when the physically based approach is adopted in regional scale area, the uncertainties were involved in the analysis procedure due to spatial variation and complex geological conditions, which causes inaccurate analysis results. Therefore, probabilistic method have been used to quantify these uncertainties. However, the uncertainties caused by lack of information are not dealt with the probabilistic analysis. Therefore, fuzzy set theory was adopted in this study because the fuzzy set theory is more effective to deal with uncertainties caused by lack of information. In addition, the vertex method and Monte Carlo simulation are coupled with the fuzzy approach. The proposed approach was used to evaluate the landslide susceptibility for a regional study area. In order to compare the analysis results of the proposed approach, Monte Carlo simulation as the probabilistic analysis and the deterministic analysis are used to analyze the landslide susceptibility for same study area. We found that Fuzzy Monte Carlo simulation showed the better prediction accuracy than the probabilistic analysis and the deterministic analysis.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.561-577
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• 2021

The compacted bentonite buffer in a geological repository for high-level radioactive waste disposal is saturated due to groundwater inflow. Saturation of the bentonite buffer results in bentonite swelling and bentonite penetration into the rock discontinuities present around the disposal hole. The penetrated bentonite is exposed to groundwater flow and can be eroded out of the repository, resulting in bentonite mass loss which can affect the physical integrity of the engineered barrier system. Hence, the evaluation of buffer-rock interactions and coupled behavior due to groundwater inflow and bentonite penetration is necessary to ensure long-term disposal safety. In this study, the effects of the bentonite penetration and swelling on the physical properties of jointed rock mass were evaluated using the quasi-static resonant column test. Jointed rock specimens with bentonite penetration were manufactured using Gyeongju bentonite and hollow cylindrical granite rock discs obtained from the KAERI underground research tunnel. The effects of vertical stress and saturation were assessed using the P-wave and S-wave velocities for intact rock, jointed rock and jointed rock with bentonite penetration specimens. The joint normal and joint shear stiffnesses of each joint condition were inferred from the wave velocity results assuming an equivalent continuum. The joint normal and joint shear stiffnesses obtained from this study can be used as input factors for future numerical analysis on the performance evaluation of geological waste disposal considering rock discontinuities.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Applied Chemistry for Engineering
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• v.27 no.1
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• pp.92-100
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• 2016

Low-temperature conversion of nitrogen oxides using plasma-assisted hydrocarbon selective catalytic reduction of (HC-SCR) was investigated. Plasma was created in the catalyst-packed bed so that it could directly interact with the catalyst. The effect of the reaction temperature, the shape of catalyst, the concentration of n-heptane as a reducing agent, the oxygen content, the water vapor content and the energy density on $NO_x$ removal was examined. $NO_x$ conversion efficiencies achieved with the plasma-catalytic hybrid process at a temperature of $250^{\circ}C$ and an specific energy input (SIE) of $42J\;L^{-1}$ were 83% and 69% for one-dimensional Ag catalyst ($Ag\;(nanowire)/{\gamma}-Al_2O_3$) and spherical Ag catalyst ($Ag\;(sphere)/{\gamma}-Al_2O_3$), respectively, whereas that obtained with the catalyst-alone was considerably lower (about 30%) even with $Ag\;(nanowire)/{\gamma}-Al_2O_3$ under the same condition. The enhanced catalytic activity towards $NO_x$ conversion in the presence of plasma can be explained by the formation of more reactive $NO_2$ species and partially oxidized hydrocarbon intermediates from the oxidation of NO and n-heptane under plasma discharge. Increasing the SIE tended to improve $NO_x$ conversion efficiency, and so did the increase in the n-heptane concentration; however, a further increase in the n-heptane concentration beyond $C_1/NO_x$ ratio of 5 did not improve the $NO_x$ conversion efficiency any more. The increase in the humidity affected negatively the $NO_x$ conversion efficiency, resulting in lowering the $NO_x$ conversion efficiency at the higher water vapor content, because water molecules competed with $NO_x$ species for the same active site. The $NO_x$ conversion efficiency increased with increasing the oxygen content from 3 to 15%, in particular at low SIE values, because the formation of $NO_2$ and partially oxidized hydrocarbon intermediates was facilitated.

• Journal of Environmental Policy
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• v.9 no.2
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• pp.157-184
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• 2010

Global climate change is destroying the water circulation balance by changing rates of precipitation, recharge and discharge, and evapotranspiration. The Intergovernmental Panel on Climate Change (IPCC 2007) makes "changes in rainfall pattern due to climate system changes and consequent shortage of available water resource" a high priority as the weakest part among the effects of human environment caused by future climate changes. Groundwater, which occupies a considerable portion of the world's water resources, is related to climate change via surface water such as rivers, lakes, and marshes, and "direct" interactions, being indirectly affected through recharge. Therefore, in order to quantify the effects of climate change on groundwater resources, it is necessary to not only predict the main variables of climate change but to also accurately predict the underground rainfall recharge quantity. In this paper, the authors selected a relevant climate change scenario, In this context, the authors selected A1B from the Special Report on Emission Scenario (SRES) which is distributed at Korea Meteorological Administration. By using data on temperature, rainfall, soil, and land use, the groundwater recharge rate for the research area was estimated by period and embodied as geographic information system (GIS). In order to calculate the groundwater recharge quantity, Visual HELP3 was used as main model for groundwater recharge, and the physical properties of weather, temperature, and soil layers were used as main input data. General changes to water circulation due to climate change have already been predicted. In order to systematically solve problems associated with how the groundwater resource circulation system should be reflected in future policies pertaining to groundwater resources, it may be urgent to recalculate the groundwater recharge quantity and consequent quantity for using via prediction of climate change in Korea in the future and then reflection of the results. The space-time calculation of changes to the groundwater recharge quantity in the study area may serve as a foundation to present additional measures for the improved management of domestic groundwater resources.