• KSBB Journal
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• v.5 no.1
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• pp.25-35
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• 1990

In the Xanthan gum fermentation by Xanthomonas campestris there are problems of the large energy consumption by long fermentation time, the mass transfer of oxygen and nutrients by high viscous fermentation broth. In this study, the media optimization and the fed batch fermentation were carried out to decrease fermentation time and increase Xanthan gum yield. The $O_2$ uptake rate (OUR) and $CO_2$ evolution rate(CER) which were obtained from the analysis of fermentation exit gas using a gas chromatograph were investigated. As a result, the fermentation time decreased at optimal assimilable nitrogen concentration but increased at poor or rich assimilable nitrogen concentration, the Xanthan gum biosynthesis was stimulated under the limited condition of assimilable nitrogen source and the optimum fermentation medium was obtained as follow; Glucose=30g / l, Peptone=8.0g / l, $K_2HPO_4=2.0g/l$, $MgS0_47H_2O=10g/l$, Sodium acetate=20g/l, Sodium pyruvate=0.5g/1. As the agitation speed and nitrogen concentration increased, the $O_2$ uptake rate and $CO_2$ evolution rate increased. The OUR and CER were 37.3mmol $O_2/\;l$ hr and 20.2 mmol $CO_2/\;L$ hr at peptone 11g / l and agitation speed 990RPM, respectively. In fed batch fermentation, the final concentration of Xanthan gum was enhanced up to 29g / l.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.291-291
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• 2010

Organic solar cells have attracted much interest due to the potential advantage of the lightness, simple solution processing and flexibility. Until recently, the focus of organic solar cells research has been on optimization of material processing to improve the power conversion efficiency. However, area scaling is an important position for alternative to the market dominating solar cells. Spray deposition technologies have advantage of less material wastage and possibility of large scale photoactive area coating when compared with spin coating process. We investigated the performance of organic solar cells as a function of active area using two types of deposition process. The commonly used process is spin coating which can be fabricated organic materials deposition for devices. Spray deposition process compare with spin coating for large-area organic solar cells. The spray deposition organic layer shows excellent performance up to the active area of $4\;cm^2$ with the PCE of ~3.0 % under AM.1.5 simulated illumination with an intensity of $100mW/cm^2$. This indicates that the spray deposition process can be used as a mass production process for evaluating large-area organic solar cells.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.9
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• pp.135-141
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• 2004

Anti-shock performance is one of the most important design specifications of TFT-LCD modules. Since they are adopted fur major display units of many mobile applications such as lap-top PCs, cellular phones, and palm pilots, they are able to accommodate and endure high level transient mechanical energy inputs. For the reasons, not only the LCD unit manufacturers but their customers like PC makers perform a series of strict impact/drop test on the units. Currently, designers are mostly relying on their own trial-error based experience for the anti-shock design. Thus those designs depending on only experience may result in disqualification from the drop/impact test during final product evaluation. Those shock failures of any new designs are prohibitive for both LCD and PC manufacturers. In order to avoid this problem, many designers are focusing on the development of computer-aided design tools that is directly connected to shock simulation capabilities and then shock-proof design cycle time could be significantly reduced. Development of an integrated CAE system for the shock-proof design is presented in this article. At every stages of the development of present work, practical industrial applicability and mass production feasibility are seriously considered and tested so that the system is to be used in the LCD design engineering field.

• Journal of the Korean Society of Visualization
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• v.17 no.1
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• pp.43-52
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• 2019

'Ionic wind' is phenomenon induced by corona discharge which occurs when large electric potential is applied to electrodes with high curvature. The ionic wind has advantage that it could generate forced convective flow without any external energy like separate pump. In this study, 'pin-mesh' arrangement is utilized for experiments. First, optimization of configuration is conducted with local momentum of ionic wind behind the mesh. Empirical equation for prediction about velocity profile was derived using the measured results. Secondly, the enhancement of mass transfer rate of acetone with ionic wind was analyzed. Also, the drying efficiency using a fan which has same flow rate was compared with ionic wind for identification of additional chemical reaction. At last, the drying process of organic solvent was visualized with image processing. As a result, it was shown that the use of ionic wind could dry organic matter four times faster than the natural condition.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.154-164
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• 2019

A rotor dynamic analysis is mandatory for stability and design optimization of submerged propellers and turbines. An accurate simulation requires a proper consideration of fluid-induced reaction forces. This paper presents a bi-directional coupling of a bond graph method solver and an unsteady vortex lattice method solver where the former is used to model the rotor dynamics of the power train and the latter is used to predict transient hydrodynamic forces. Due to solver coupling, determination of hydrodynamic coefficients is obsolete and added mass effects are considered automatically. Additionally, power grid and structural faults like grid fluctuations, eccentricity or failure could be investigated using the same model. In this research work a fast, time resolved dynamic simulation of the complete power train is conducted. As an example, the rotor dynamics of a tidal stream turbine is investigated under two inflow conditions: I - shear flow, II - shear flow + water waves.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.654-660
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• 2011

One of the best way to control Combined Sewer Overflow (CSO) is proposed to construct first flush storage tank. But there is little known parameters for optimum design of these facilities. This study was conducted to get optimum design parameters for a first flush storage tank construction. The optimization of the tank is generally based upon some measure of SS(Suspended Solid) mass holding efficiency. Water quality deterioration of receiving water body happened right after first time occurring rainfall in dry weather seasons. So, design rainfall intensity is used at 2 mm/hr for peak of monthly average intensities of dry seasons. The capacities for each evaluated catchment are designed from 14.4 min to 16.1 min HRT of CSOs flow at design rainfall intensity. Owing to all storage tanks are connected to interception sewer having a redundancy, the suggested volume could be cut down.

• Food Science and Industry
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• v.50 no.1
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• pp.16-25
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• 2017

There is no doubt that accumulation of big data using multi-omics technologies will be useful to solve human's long-standing problems such as development of personalized diet and medicine, overcoming diseases, and longevity. However, in the food industry, big data based on omics is scarcely accumulated. In particular, comprehensive analysis of molecular lipid metabolites directly associated with food quality, such as taste, flavor, and texture has been very limited. Moreover, most of food lipidomics studies are applied to analyze lipid components and discriminate authenticity and freshness of limited foods including vegetable and fish oil. However, if lipid big data through food lipidomics research of various foods and materials can be accumulated, lipidomics can be used in the optimization of food processing, production, delivery system, food safety, and storage as well as functional food.

• Korean Journal of Chemical Engineering
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• v.35 no.11
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• pp.2321-2326
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• 2018

We evaluated the optimal conditions for fluidization of nickel oxide (NiO) and its reduction into high-purity Ni during hydrogen reduction in a laboratory-scale fluidized bed reactor. A comparative study was performed through structural shape analysis using scanning electron microscopy (SEM); variance in pressure drop, minimum fluidization velocity, terminal velocity, reduction rate, and mass loss were assessed at temperatures ranging from 400 to $600^{\circ}C$ and at 20, 40, and 60 min in reaction time. We estimated the sample weight with most active fluidization to be 200 g based on the bed diameter of the fluidized bed reactor and height of the stocked material. The optimal conditions for NiO hydrogen reduction were found to be height of sample H to the internal fluidized bed reactor diameter D was H/D=1, reaction temperature of $550^{\circ}C$, reaction time of 60 min, superficial gas velocity of 0.011 m/s, and pressure drop of 77 Pa during fluidization. We determined the best operating conditions for the NiO hydrogen reduction process based on these findings.

• Smart Structures and Systems
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• v.28 no.6
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Analytical Science and Technology
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• v.35 no.2
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• pp.60-68
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• 2022

In this study, we developed and validated a sensitive analytical method to quantify baphicacanthin A in mouse plasma using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The standard calibration curves for baphicacanthin A ranged from 0.5 to 200 ng/mL and were linear, with an r² of 0.985. The inter- and intra-day accuracy and precision and the stability fell within the acceptance criteria. Besides, we investigated the pharmacokinetics of baphicacanthin A following its intravenous (5 mg/kg) and oral administration (30 mg/kg). Intravenously injected baphicacanthin A showed biphasic elimination kinetics with high clearance and volume of distribution values. Furthermore, baphicacanthin A showed a rapid absorption but low aqueous solubility (182.51±0.20 mg/mL), resulting in low plasma concentrations and low oral bioavailability (2.49 %). Thus, we successfully documented the pharmacokinetic properties of baphicacanthin A using this newly developed sensitive LC-MS/MS quantification method, which could be used in future lead optimization and biopharmaceutic studies.