• Clean Technology
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• v.30 no.3
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• pp.228-238
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• 2024

Electrolytes are one of the essential components of a lithium-ion battery. They determine the battery's lifespan and cell characteristics. The dielectric constant is a key thermophysical property for determining how much salt can be dissociated and solvated in a solution. Hence, fast and reliable dielectric constant measurement is essential when formulating an electrolyte solution. This work implemented an open-ended coaxial probe (OECP) station as a quick and reliable tool to measure the complex permittivity spectra of electrolyte solutions. The capability of the OECP station was tested by measuring the complex permittivity of propylene carbonate (PC), dimethyl carbonate (DMC), and their mixtures from 0.1 to 8 GHz at 288.15, 298.15, and 308.15 K. The obtained dielectric spectra were then interpreted based on dielectric relaxation models and thermodynamic theories. The measured static dielectric constant data agreed well with the data from previous studies. They were also correlated using the Wang-Anderko thermodynamic model, showing approximately a 1% deviation from the experimental data. In addition, the relaxation characteristics, including the relaxation time and the Cole-Davidson exponent, showed that the microstructure of the solution significantly changes at the propylene carbonate mole fraction of 0.4. These results and methodologies are expected to contribute to the further understanding of electrolyte solutions and ultimately lead to the optimization of electrolyte formulation for lithium-ion batteries.

• Microbiology and Biotechnology Letters
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• v.37 no.3
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• pp.231-237
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• 2009

This paper aimed to develop a solvent extraction and purification process to recover high-purified ${\beta}$-carotene from recombinant Escherichia coli. Cells harvested from the culture broth were treated through numerous steps: dehydration, solvent extraction, crystal formation and separation. To optimize the extracting condition, experiments were carried out to investigate the effect of cell disruption, temperature, organic solvents, solvent-biomass ratio on the yield of ${\beta}$-carotene extracted from cells. The result indicated that no significant differences of extraction yield were observed from cells with or without step of cell disruption. Among different extracting solvents, the highest extraction yield of ${\beta}$-carotene, 30.3 mg-${\beta}$-carotene/g-dry cells, was obtained with isobutyl acetate at solvent-biomass ratio 25 mL/g-dry cells at $50^{\circ}C$. Notably, in case of acetone, the extraction yield was quite low when using acetone itself, but increased almost up to the highest value when combining this solvent and olive oil. The purity of ${\beta}$-carotene crystals obtained from crystallization and separation was 89%. The purity degree was further improved up to 98.5% by treating crude crystals with additional ethanol washing.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.1
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• pp.25-31
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• 2011

In this study, model-based $NH_4-N$ predictive control algorithm by using influent pattern was developed and evaluated for effective control application in $A^2/O$ process. A pilot-scale $A^2/O$process at S wastewater treatment plant in B city was selected. The behaviors of organic, nitrogen and phosphorous in the biological reactors were described by using the modified ASM3+Bio-P model. A one-dimensional double exponential function model was selected for modeling of the secondary settlers. The effluent $NH_4-N$ concentration on the next day was predicted according to model-based simulation by using influent pattern. After the objective effluent quality and simulation result were compared, the optimal operational condition which able to meet the objective effluent quality was deduced through repetitive simulation. Next the effluent $NH_4-N$ control schedule was generated by using the optimal operational condition and this control schedule on the next day was applied in pilot-scale $A^2/O$ process. DO concentration in aerobic reactor in predictive control algorithm was selected as the manipulated variable. Without control case and with control case were compared to confirm the control applicability and the study of the applied $NH_4-N$control schedule in summer and winter was performed to confirm the seasonal effect. In this result, the effluent $NH_4-N$concentration without control case was exceeded the objective effluent quality. However the effluent $NH_4-N$ concentration with control case was not exceeded the objective effluent quality both summer and winter season. As compared in case of without predictive control algorithm, in case of application of predictive control algorithm, the RPM of air blower was increased about 9.1%, however the effluent $NH_4-N$ concentration was decreased about 45.2%. Therefore it was concluded that the developed predictive control algorithm to the effluent $NH_4-N$ in this study was properly applied in a full-scale wastewater treatment process and was more efficient in aspect to stable effluent.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.61-77
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• 2019

If a new utility tunnel is planned for high density existing urban areas in Korea, a rational decision-making process such as the determination of optimum design capacity by using the feasibility evaluation system based on quantitative evaluation indexes and the economic evaluation is needed. Thus, the previous study presented the important weight of individual higher-level indexes (3 items) and sub-indexes (16 items) through a hierarchy analysis (AHP) for quantitative evaluation index items, considering the characteristics of each urban type. In addition, an economic evaluation method was proposed considering 10 benefit items and 8 cost items by adding 3 new items, including the effects of traffic accidents, noise reduction and socio-economic losses, to the existing items for the benefit cost analysis suitable for urban utility tunnels. This study presented a quantitative feasibility evaluation method using the important weight of 16 sub-index items such as the road management sector, public facilities sector and urban environment sector. Afterwards, the results of quantitative feasibility and economic evaluation were compared and analyzed in 123 main road sections of the Seoul. In addition, a comprehensive evaluation method was proposed by the combination of the two evaluation results. The design capacity optimization program, which will be developed by programming the logic of the quantitative feasibility and economic evaluation system presented in this study, will be utilized in the planning and design phases of urban community zones and will ultimately contribute to the vitalization of urban utility tunnels.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.379-394
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• 2021

Air pollution data in South Korea is provided on a real-time basis by Air Korea stations since 2005. Previous studies have shown the feasibility of gridding air pollution data, but they were confined to a few cities. This paper examines the creation of nationwide gridded maps for PM10 concentration using 333 Air Korea stations with variogram optimization and ordinary kriging. The accuracy of the spatial interpolation was evaluated by various sampling schemes to avoid a too dense or too sparse distribution of the validation points. Using the 114,745 matchups, a four-round blind test was conducted by extracting random validation points for every 365 days in 2019. The overall accuracy was stably high with the MAE of 5.697 ㎍/m³ and the CC of 0.947. Approximately 1,500 cases for high PM10 concentration also showed a result with the MAE of about 12 ㎍/m³ and the CC over 0.87, which means that the proposed method was effective and applicable to various situations. The gridded maps for daily PM10 concentration at the resolution of 0.05° also showed a reasonable spatial distribution, which can be used as an input variable for a gridded prediction of tomorrow's PM10 concentration.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.8 no.4
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• pp.599-604
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• 1998

We have investigated Pt and $RuO_2$ as a bottom electrode for ferroelectric capacitor applications. The bottom electrodes were prepared by using an RF magnetron sputtering method. Some of the investigated parameters were a substrate temperature, gas flow rate, RF power for the film growth, and post annealing effect. The substrate temperature strongly influenced the surface morphology and resistivity of the bottom electrodes as well as the film crystallographic structure. XRD results on Pt films showed a mixed phase of (111) and (200) peak for the substrate temperature ranged from RT to $200^{\circ}C$, and a preferred (111) orientation for $300^{\circ}C$. From the XRD and AFM results, we recommend the substrate temperature of $300^{\circ}C$ and RF power 80W for the Pt bottom electrode growth. With the variation of an oxygen partial pressure from 0 to 50%, we learned that only Ru metal was grown with 0~5% of $O_2$ gas, mixed phase of Ru and $RuO_2$ for $O_ 2$ partial pressure between 10~40%, and a pure $RuO_2$ phase with $O_2$ partial pressure of 50%. This result indicates that a double layer of $RuO_2/Ru$ can be grown in a process with the modulation of gas flow rate. Double layer structure is expected to reduce the fatigue problem while keeping a low electrical resistivity. As post anneal temperature was increased from RT to $700^{\circ}C$, the resistivity of Pt and $RuO_2$ was decreased linearly. This paper presents the optimized process conditions of the bottom electrodes for memory device applications.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1043-1060
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• 2023

An acceleration of climate change in recent years has led to increased attention towards 'blue carbon' which refers to the carbon captured by the ocean. However, our comprehension of marine ecosystems is still incomplete. This study classified and analyzed global marine eco-provinces using k-means clustering considering carbon cycling. We utilized five input variables during the past 20 years (2001-2020): Carbon-based Productivity Model (CbPM) Net Primary Production (NPP), particulate inorganic and organic carbon (PIC and POC), sea surface salinity (SSS), and sea surface temperature (SST). A total of nine eco-provinces were classified through an optimization process, and the spatial distribution and environmental characteristics of each province were analyzed. Among them, five provinces showed characteristics of open oceans, while four provinces reflected characteristics of coastal and high-latitude regions. Furthermore, a qualitative comparison was conducted with previous studies regarding marine ecological zones to provide a detailed analysis of the features of nine eco-provinces considering carbon cycling. Finally, we examined the changes in nine eco-provinces for four periods in the past (2001-2005, 2006-2010, 2011-2015, and 2016-2020). Rapid changes in coastal ecosystems were observed, and especially, significant decreases in the eco-provinces having higher productivity by large freshwater inflow were identified. Our findings can serve as valuable reference material for marine ecosystem classification and coastal management, with consideration of carbon cycling and ongoing climate changes. The findings can also be employed in the development of guidelines for the systematic management of vulnerable coastal regions to climate change.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.434-441
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• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.1
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• pp.11-26
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• 1984

The aim of this study is to establish a synthetical optimal method that simultaneously analyze and design reinforced concrete flat slab-column structures involving multi-constraints and multi-design variables. The variables adopted in this mathematical models consist of design variables including sectional sizes and steel areas of frames, and analysis variable of the ratio of bending moment redistribution. The cost function is taken as the objective function in the formulation of optimal problems. A number of constraint equations, involving the ultimate limit state and the serviceability limit state, is derived in accordance with BSI CP110 requirements on the basis of limit state design theory. Both objective function and constraint equations derived from design variables and an analysis variable generally become high degree nonlinear problems. Using SLP as an analytical method of nonlinear optimal problems, an optimal algorithm is developed so as to analyze and design the structures considered in this study. The developed algorithm is directly applied to a few reinforced concrete flat slab-column structures to assure the validity of it and the possibility of optimization From the research it is found that the algorithm developed in this study is applicable to the optimization of reinforced concrete flat slab column structures and it converges to a optimal solution with 4 to 6 iterations regardless of initial variables. The result shows that an economical design can be possible when compared with conventional designs. It is also found that considering the ratio of bending moment redistribution as a variable is reasonable. It has a great effect on the composition of optimal sections and the economy of structures.

• Journal of the Korean Society of Radiology
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• v.9 no.1
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• pp.47-53
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• 2015

Quantitative analysis of MR spectrum depending on mole concentration of the contrast media in cereberal metabolite phantom was performed. PRESS pulse sequence was used to obtain MR spectrum at 3.0T MRI system (Archieva, Philips Healthcare, Best, Netherland), and the phantom contains brain metabolites such as N-Acetyl Asparatate (NAA), Choline (Cho), Creatine (Cr) and Lactate (Lac). In this study, optimization of MRS PRESS pulse sequency depending on the concentration of contrast media (0, 0.1 and $0.3mmol/{\ell}$) was evaluated for various repetition time(TR; 1500, 1700 and 2000 ms). In control (cotrast-media-free) group, NAA and Cho signals were the highest at TR 2000 ms than at 1700 and 1500 ms. Cr had the highest peak signal at TR 1500 ms. When concentration of contrast media was $0.1mmol/{\ell}$, the metabolites were increased NAA 73%, Cho 249%, Cr 37% at TR 1700 ms compared with other TR, and also signal increased at $0.3mmol/{\ell}$, In $0.5mmol/{\ell}$ of contrast agent, cerebral metabolite peaks reduced, especially when TR 1500 ms and 2000 ms they decreased below those of control group. The ratio of metabolite peaks such as NAA/Cr and Cho/Cr decreased as the concentration of the contrast agent increased from 0.1 to $0.5mmol/{\ell}$. Authors found that the optimization of PRESS sequence for 0.3T MRS was as follows: low density of contrast agent ($0.1mmol/{\ell}$ and $0.3mmol/{\ell}$) made the highest signal intensity, while high density of contrast agent reveals the least reduction of signal intensity at 1700 ms. In conclusion, authors believe that it is helpful to reduce TR for acquiring maximum signal intensity.