• Journal of Korean Society of Environmental Engineers
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• v.34 no.3
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• pp.189-194
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• 2012

In this study, a 3-stage biological aerated filter (BAF) system was proposed to enhance nitrogen removal in the treatment of low carbon to nitrogen ratio (C/N ratio) municipal wastewater. Laboratory experiments were conducted to evaluate the effects of dynamic-flow at the HRT of 6 h. Results of the long-term operation of 3-stage BAF systems showed that the dynamic-flow enabled the total nitrogen removal (T-N) removal efficiency of the system to be about 7 % higher than that of non-dynamic-flow system in treating domestic wastewater due to the more efficient use of organic substrates. The overall $NH_4$-N removal performance was stable during the operational period due to the unique system configuration where independent nitrification occurred. It was concluded that the 3-stage BAF system proposed in this study provided excellent performance in the removal of nitrogen by employing dynamic-flow and three columns functioning as sorption, denitrification and nitrification, respectively.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.12
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• pp.1081-1088
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• 2009

The performance of a electrocoagulation (EC) process was examined for the removal of Rhodamine B (RhB) using iron electrode. The effects of operational parameters such as electrode material (aluminum and iron), current density, NaCl dosage, intial pH and initial dye concentration on RhB removal efficiency were investigated. The optimum range for each of these operating variables were experimentally determined. The experimental results showed that the iron is superior to aluminum as sacrificial electrode material. The optimum time of electrolysis, current density, NaCl dosage and pH were 10 min, 1630 A/$m^2$, 4 g/L and neutral pH, respectively. Under these conditions, RhB was effectively removed (> 93.4%) and also more than 80% of COD was removed (> 88.9%) when the initial concentration of RhB was 230 mg/L. The electrical energy consumption in the above conditions for the color and COD of RhB removal were 10.3 and 10.8 kWh/kg RhB, respectively. The electrocoagulation process could be a promising technology to treat dye wastewater containing RhB.

• Journal of Microbiology and Biotechnology
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• v.20 no.12
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• pp.1717-1723
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• 2010

The integrated fixed-film activated sludge (IFAS) system is a variation of the activated sludge wastewater treatment process, in which hybrid suspended and attached biomass is used to treat wastewater. Although the function and performance of the IFAS system are well studied, little is known about its microbial community structure. In this study, the composition and diversity of the bacterial community of suspended and attached biomass samples were investigated in a full-scale IFAS system using a high-throughput pyrosequencing technology. Distinct bacterial community compositions were examined for each sample and appeared to be important for its features different from conventional activated sludge processes. The abundant bacterial groups were Betaproteobacteria (59.3%), Gammaproteobacteria (8.1%), Bacteroidetes (5.2%), Alphaproteobacteria (3.9%), and Actinobacteria (3.2%) in the suspended sample, whereas Actinobacteria (14.6%), Firmicutes (13.6%), Bacteroidetes (11.6%), Betaproteobacteria (9.9%), Gammaproteobacteria (9.25%), and Alphaproteobacteria (7.4%) were major bacterial groups in the attached sample. Regarding the diversity, totals of 3,034 and 1,451 operational taxonomic units were identified at the 3% cutoff for the suspended and attached samples, respectively. Rank abundance and community analyses demonstrated that most of the diversity was originated from rare species in the samples. Taken together, the information obtained in this study will be a base for further studies relating to the microbial community structure and function of the IFAS system.

• Smart Structures and Systems
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• v.29 no.1
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• pp.17-28
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• 2022

The cable component of cable-stayed bridges is gradually impacted by weather conditions, vehicle loads, and material corrosion. The stayed cable is a critical load-carrying part that closely affects the operational stability of a cable-stayed bridge. Damaged cables might lead to the bridge collapse due to their tension capacity reduction. Thus, it is necessary to develop structural health monitoring (SHM) techniques that accurately identify damaged cables. In this work, a combinational identification method of three efficient techniques, including statistical analysis, clustering, and neural network models, is proposed to detect the damaged cable in a cable-stayed bridge. The measured dataset from the bridge was initially preprocessed to remove the outlier channels. Then, the theory and application of each technique for damage detection were introduced. In general, the statistical approach extracts the parameters representing the damage within time series, and the clustering approach identifies the outliers from the data signals as damaged members, while the deep learning approach uses the nonlinear data dependencies in SHM for the training model. The performance of these approaches in classifying the damaged cable was assessed, and the combinational identification method was obtained using the voting ensemble. Finally, the combination method was compared with an existing outlier detection algorithm, support vector machines (SVM). The results demonstrate that the proposed method is robust and provides higher accuracy for the damaged cable detection in the cable-stayed bridge.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.299-305
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• 2015

Global environmental concerns and the ever increasing need of energy, coupled with steady progress in renewable energy technologies, are opening up new opportunities for utilization of renewable energy resources. Distributed electricity generation is a suitable option for sustainable development thanks to the load management benefits and the opportunity to provide electricity to remote areas. Solar energy being easy to harness, non-polluting and never ending is one of the best renewable energy sources for electricity generation in present and future time. Due to the random and intermittent nature of solar source, PV plants require the adoption of an energy storage and management system to compensate fluctuations and to meet the energy demand during night hours. This paper presents an efficient, economic and technical model for the design of a MPPT based grid connected PV with battery storage and management system. This system satisfies the energy demand through the PV based battery energy storage system. The aim is to present PV-BES system design and management strategy to maximize the system performance and economic profitability. PV-BES (photovoltaic based battery energy storage) system is operated in different modes to verify the system feasibility. In case of excess energy (mode 1), Li-ion batteries are charged using CC-CV mechanism effectively controlled by fuzzy logic based PID control system whereas during the time of insufficient power from PV system (mode 2), batteries are used as backup to compensate the power shortage at load and likewise other modes for different scenarios. This operational mode change in PV-BES system is implemented by State flow chart technique based on SOC, DC bus voltages and solar Irradiance. Performance of the proposed PV-BES system is verified by some simulations study. Simulation results showed that proposed system can overcome the disturbance of external environmental changes, and controls the energy flow in efficient and economical way.

• Journal of Animal Environmental Science
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• v.4 no.2
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• pp.161-166
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• 1998

Controlling malodor originating from livestock feces has become a major issue, due to its influence on the health of man and livestock, together with its influences on atmospheric pollution. In this study, Five types of biofilters filled with saw-dust, night soil, fermented compost, leaf mold and a mixture(a compound of night soil, fermented compost and leaf mold at the same rates, respectively) were manufactured and tested. To study the effect of the biofilter on reducing malodor in a composting facility and swine building, a pilot scale composting facility enclosed with polyethylene film was constructed. Swine feces was composted in the facility and malodorous gas generated from the decomposition of organic matter in the feces was gathered by vacuum pump. Each biofilter achieved 87∼96% NH3 removal efficiency. This performance was maintained throughout 10 days of operation. The highest NH3 removal efficiency was achieved by leaf mold on the first day of operation period. It reduced the concentration of NH3 by about 96%. Night soil and fermented compost showed nearly equal performance of 93 to 94% for 10 days from the beginning of operation. The mixture achieved the lowest NH3 removal efficiency. It reduced NH3 concentration by about 89∼94% for 10 days from the beginning of operation. However NH3 removal efficiency of each biofilter declined with the passage of operational time. After 30 days from the beginning of operation, NH3 removal efficiency of each biofilter of each biofilter was below 60%, respectively. The concentration of H2S and CH3-SH originating from compost were equal to or less than 5mg/l and 3mg/l, respectively. After passing throughout the biofilter, the concentration of H2S and CH3-SH were not detected.

• Environmental Engineering Research
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• v.24 no.2
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• pp.263-270
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• 2019

Palm oil mill effluent (POME) is the largest pollutant discharged into the rivers of Malaysia. Thus UF membrane study was conducted to investigate the effect of pressure and stirring speed on performance of POME treatment and fouling of membrane. Two types of membrane polyethersulfone (PES) and regenerated cellulose (RC) with molecular weight cut-off (MWCO) 5 and 10 kDa were used in this study. Results showed that, as pressure increased, fouling increased however permeate quality improved, the best pressure was 1.0 bar, where the fouling was not too high and produce good permeate quality. As stirring speed increased, fouling reduced and permeate quality improved, however, when stirring speed increased from 600 rpm to 800 rpm, there was no significant improvement on the permeate quality. Therefore, the best condition was at 1.0 bar and 600 rpm. PES membrane with MWCO 5 kDa showed the best permeate quality, even fouling slightly higher than RC membrane. The permeate quality obtained were analyzed in term of dissolved solid, turbidity, suspended solid, biological oxygen demand ($BOD_5$) and chemical oxygen demand (COD) were 538 mg/L, 1.02 NTU, < 25 mg/L, 27.7 mg/L and 62.8 mg/L, respectively with dominant type of fouling is cake resistance. Thus, it can be concluded water reuse standard was successfully achieved in terms of $BOD_5$ and suspended solid.

• Atmosphere
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• v.33 no.5
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• pp.531-548
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• 2023

We developed the Aviation Convective Index (ACI) for predicting deep convective area using the operational global Numerical Weather Prediction model of the Korea Meteorological Administration. Seasonally optimized ACI (ACI_SnOpt) was developed to consider seasonal variabilities on deep convections in Korea. Yearly optimized ACI (ACI_YrOpt) in Part 1 showed that seasonally averaged values of Area Under the ROC Curve (AUC) and True Skill Statistics (TSS) were decreased by 0.420% and 5.797%, respectively, due to the significant degradation in winter season. In Part 2, we developed new membership function (MF) and weight combination of input variables in the ACI algorithm, which were optimized in each season. Finally, the seasonally optimized ACI (ACI_SnOpt) showed better performance skills with the significant improvements in AUC and TSS by 0.983% and 25.641% respectively, compared with those from the ACI_YrOpt. To confirm the improvements in new algorithm, we also conducted two case studies in winter and spring with observed Convectively-Induced Turbulence (CIT) events from the aircraft data. In these cases, the ACI_SnOpt predicted a better spatial distribution and intensity of deep convection. Enhancements in the forecast fields from the ACI_YrOpt to ACI_SnOpt in the selected cases explained well the changes in overall performance skills of the probability of detection for both "yes" and "no" occurrences of deep convection during 1-yr period of the data. These results imply that the ACI forecast should be optimized seasonally to take into account the variabilities in the background conditions for deep convections in Korea.

• Journal of Soil and Groundwater Environment
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• v.29 no.4
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• pp.12-20
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• 2024

Diffusive gradients in thin films (DGT) are passive sampling devices used to determine the time-weighted average concentrations (TWAC) of contaminants. To ensure accurate performance in groundwater, it is crucial to identify environmental characteristics and maintain optimal operational conditions. This study examined the deployment time required to reach effective capacity, the thickness of the diffusive boundary layer (DBL) under stagnant water conditions, and biofilm formation on the DGT surface using groundwater samples. When using DGT with Chelex gel (A=3.14 cm²), the effective capacity was 0.7 ㎍ for Cd and 250 ㎍ for Zn, with a deployment time of 24 h. Lower Cd accumulation was due to the competition effect of coexisting ions. The DBL thickness under stagnant conditions was 0.074 cm, 93% of the diffusion gel's thickness (0.08 cm). Neglecting DBL thickness in TWAC calculations led to a 79% decrease in the determined concentration. No biofouling was observed during the 28-d DGT deployment in groundwater. In conclusion, it is essential to consider the appropriate deployment time, DBL thickness, and biofilm formation to ensure accurate DGT performance in determining contaminant levels in groundwater.

• Proceedings of the KSRS Conference
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• v.1
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• pp.278-281
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• 2006

Korea Meteorological Administration(KMA) has issued the tropical storm(typhoon) warning or advisories when it was developed to tropical storm from tropical depression and a typhoon is expected to influence the Korean peninsula and adjacent seas. Typhoon information includes current typhoon position and intensity. KMA has used the Dvorak Technique to analyze the center of typhoon and it's intensity by using available geostationary satellites' images such as GMS, GOES-9 and MTSAT-1R since 2001. The Dvorak technique is so subjective that the analysis results could be variable according to analysts. To reduce the subjective errors, QuikSCAT seawind data have been used with various analysis data including sea surface temperature from geostationary meteorological satellites, polar orbit satellites, and other observation data. On the other hand, there is an advantage of using the Subjective Dvorak Technique(SDT). SDT can get information about intensity and center of typhoon by using only infrared images of geostationary meteorology satellites. However, there has been a limitation to use the SDT on operational purpose because of lack of observation and information from polar orbit satellites such as SSM/I. Therefore, KMA has established Advanced Objective Dvorak Technique(AODT) system developed by UW/CIMSS(University of Wisconsin-Madison/Cooperative Institude for Meteorological Satellite Studies) to improve current typhoon analysis technique, and the performance has been tested since 2005. We have developed statistical relationships to correct AODT CI numbers according to the SDT CI numbers that have been presumed as truths of typhoons occurred in northwestern pacific ocean by using linear, nonlinear regressions, and neural network principal component analysis. In conclusion, the neural network nonlinear principal component analysis has fitted best to the SDT, and shown Root Mean Square Error(RMSE) 0.42 and coefficient of determination($R^2$) 0.91 by using MTSAT-1R satellite images of 2005. KMA has operated typhoon intensity analysis using SDT and AODT since 2006 and keep trying to correct CI numbers.