• Journal of the Korean Society of Safety
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• v.29 no.4
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• pp.23-27
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• 2014

The use of electromagnetic energy and non-equilibrium plasma for enhancing ignition and combustion stability is receiving increased attention recently. The conventional technologies have adapted the electrical devices to make the electromagnetic field, which resulted in various safety issues such as high-maintenance, additional high-cost system, electric shock and explosion. Therefore, an electrodeless microwave technology has an advantage for economic and reliability compared with conventional one because of no oxidation. However, the application of microwave has been still limited because of lack of interaction mechanism between flame and microwave. In this study, an experiment was performed with jet diffusion flames induced by microwaves to clarify the effect of microwave on the combustion stability and pollutant emissions. The results show that microwave induced flames enhanced the flame stability and blowout limit because of abundance of radical pool. However, NOx emission was increased monotonically with microwave intensity except 0.2 kW, and soot emission was reduced at the post flame region.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.1
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• pp.90-94
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• 2022

Metal 3D-printing technology enables the manufacture of complex features or internal structures, which is not possible in fabrication by conventional cutting methods. The most successful types of metal 3D printing have been powder bed diffusion and directed energy deposition, which use laser heads exploiting high-power laser sintering metal powder. In this study, a cost-effective optical design was proposed for a 2-kW-level fiber laser head. Only two commercial lenses, a beamsplitter and a window, are used in the laser head, satisfying the technological requirements. According to the optical design, the spot size was 2.54 mm, and the stand-off distance from the laser head was 295 mm. The intensity distribution was Gaussian. Thus, smooth power sintering was possible without any laser spot marks. Monte Carlo analysis was employed to verify the consistency of the optical performance under conventional assembly tolerance.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.456-460
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• 2021

In this study, a Non-Dispersive Infrared (NDIR) Carbon Dioxide (CO₂) sensor with an externally exposed optical cavity is proposed for improving sensitivity. NDIR CO₂ sensors with high performance must use a lamp-type infrared (IR) source with a strong IR intensity. However, a lamp-type IR source generates high thermal energy that induces thermal noise, interfering with the accuracy of the CO₂ concentration measure. To solve this problem, the optical cavity of the NDIR CO₂ sensor is exposed to quickly dissipate heat. As a result, the proposed NDIR CO₂ sensor has a shorter warm-up time and a higher sensitivity compared to the conventional NDIR CO₂ sensor.

• Journal of Energy Engineering
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• v.2 no.3
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• pp.268-275
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• 1993

A series of parametric investigations are performed in order to resolve the flow characteristic of a Quebec city stoker incinerator. The parameters considered in this study are five internal configurations of the Quebec city stoker itself and its modified ones, primary air velocity, the injection velocity and angle of the secondary air, and the reduction of the stoker exit area. A control-volume based finite-difference method by Patankar together with the power-law scheme is employed for discretization. The resolution of the pressure-velocity coupling is made by the use of SIMPLEC algorithm. The standard, two equation, k-$\varepsilon$ model is incorporated for the closure of turbulence. The size of recirculation region, turbulent viscosity, the mass fraction of the secondary air and pressure drop are calculated in order to analyze the characteristics of flow field. The results are physically acceptable and discussed in detail. The flow field of the Quebec city stoker shows the strong recirculation zone together with the high turbulence intensity over the upper part of the incinerator.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.667-674
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• 2007

Facial expressions provide significant clues about one's emotional state; however, it always has been a great challenge for machine to recognize facial expressions effectively and reliably. In this paper, we report a method of feature-based adaptive motion energy analysis for recognizing facial expression. Our method optimizes the information gain heuristics of ID3 tree and introduces new approaches on (1) facial feature representation, (2) facial feature extraction, and (3) facial feature classification. We use minimal reasonable facial features, suggested by the information gain heuristics of ID3 tree, to represent the geometric face model. For the feature extraction, our method proceeds as follows. Features are first detected and then carefully "selected." Feature "selection" is finding the features with high variability for differentiating features with high variability from the ones with low variability, to effectively estimate the feature's motion pattern. For each facial feature, motion analysis is performed adaptively. That is, each facial feature's motion pattern (from the neutral face to the expressed face) is estimated based on its variability. After the feature extraction is done, the facial expression is classified using the ID3 tree (which is built from the 1728 possible facial expressions) and the test images from the JAFFE database. The proposed method excels and overcomes the problems aroused by previous methods. First of all, it is simple but effective. Our method effectively and reliably estimates the expressive facial features by differentiating features with high variability from the ones with low variability. Second, it is fast by avoiding complicated or time-consuming computations. Rather, it exploits few selected expressive features' motion energy values (acquired from intensity-based threshold). Lastly, our method gives reliable recognition rates with overall recognition rate of 77%. The effectiveness of the proposed method will be demonstrated from the experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.502-508
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• 2012

Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.535-538
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• 1990

The main problem in speech recognition is the enormous variability in acoustic signals due to complex but predictable contextual effects. Especially in plosive consonants it is very difficult to find invariant cue due to various contextual effects, but humans use these contextual effects as helpful information in plosive consonant recognition. In this paper we experimented on three artificial neural net models for the recognition of plosive consonants. Neural Net Model I used "Multi-layer Perceptron ". Model II used a variation of the "Self-organizing Feature Map Model". And Model III used "Interactive and Competitive Model" to experiment contextual effects. The recognition experiment was performed on 9 Korean plosive consonants. We used VCV speech chains for the experiment on contextual effects. The speech chain consists of Korean plosive consonants /g, d, b, K, T, P, k, t, p/ (/ㄱ, ㄷ, ㅂ, ㄲ, ㄸ, ㅃ, ㅋ, ㅌ, ㅍ/) and eight Korean monothongs. The inputs to Neural Net Models were several temporal cues - duration of the silence, transition and vot -, and the extent of the VC formant transitions to the presence of voicing energy during closure, burst intensity, presence of asperation, amount of low frequency energy present at voicing onset, and CV formant transition extent from the acoustic signals. Model I showed about 55 - 67 %, Model II showed about 60%, and Model III showed about 67% recognition rate.

• Journal of Microbiology and Biotechnology
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• v.27 no.11
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• pp.2010-2018
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• 2017

Mixotrophic microalgal growth gives a great premise for wastewater treatment based on photoautotrophic nutrient utilization and heterotrophic organic removal while producing renewable biomass. There remains a need for a control strategy to enrich them in a photobioreactor. This study performed a series of batch experiments using a mixotroph, Chlorella sorokiniana, to characterize optimal guidelines of mixotrophic growth based on a statistical design of the experiment. Using a central composite design, this study evaluated how temperature and light irradiance are associated with $CO_2$ capture and organic carbon respiration through biomass production and ammonia removal kinetics. By conducting regressions on the experimental data, response surfaces were created to suggest proper ranges of temperature and light irradiance that mixotrophs can beneficially use as two types of energy sources. The results identified that efficient mixotrophic metabolism of Chlorella sorokiniana for organics and inorganics occurs at the temperature of $30-40^{\circ}C$ and diurnal light condition of $150-200{\mu}mol\;E{\cdot}m^{-2}{\cdot}s^{-1}$. The optimal specific growth rate and ammonia removal rate were recorded as 0.51/d and 0.56/h on average, respectively, and the confirmation test verified that the organic removal rate was $105mg\;COD{\cdot}l^{-1}{\cdot}d^{-1}$. These results support the development of a viable option for sustainable treatment and effluent quality management of problematic livestock wastewater.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.465-465
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• 2009

Wind power is one of the most reliable renewable energy sources and the installed wind turbine capacities are increasing radically every year. Although wind power has been favored by the public in general, the problem with the impact of wind turbine noise on people living in the vicinity of the turbines has been increased. Low noise wind turbine design is becoming more important as noise is spreading more adverse effect of wind turbine to public. This paper demonstrates the design of 10 kW class wind turbines, each of three blades, a rotor diameter 6.4m, a rated rotating speed 200 rpm and a rated wind speed 10 m/s. The optimized airfoil is dedicated for the 75% spanwise position because the dominant source of a wind turbine blade has been known as trailing edge noise from the outer 25% of the blade. Numerical computations are performed for incompressible flow and for Mach number at 0.145 and for Reynolds numbers at $1.02{\times}10^6$ with a lift performance, which is resistant to surface contamination and turbulence intensity. The objective in the low design process is to reduce noise emission, while sustaining high aerodynamic efficiency. Dominant broadband noise sources are predicted by semi-empirical formulas composed of the groundwork by Brooks et al. and Lowson associated with typical wind turbine operation conditions. During the airfoil redesign process, the aerodynamic performance is analyzed to minimize the wind turbine power loss. The results obtained from the design process show that the design method is capable of designing airfoils with reduced noise using a commercial 10 kW class wind turbine blade airfoil as a basis. The new optimized airfoil clearly indicates reduction of total SPL about 3 dB and higher aerodynamic performance.

• Korean Chemical Engineering Research
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• v.46 no.6
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• pp.1063-1068
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• 2008

The photocatalytic degradation of methylene blue water solution was carried out by irradiating microwave and UV light simultaneously using $TiO_2$ photocatalyst balls prepared by Chemical Vapor Deposition method. A microwave-discharged electrodeless UV lamp was developed to use microwave and UV simultaneously for photocatalytic reactions. The results of photocatalytic degradation of methylene blue showed that the decomposition rate increased with the microwave intensity, the circulating fluid velocity and auxiliary oxidizing agents added. Especially, the rate constant of $H_2O_2$-added photocatalytic reaction increased about three times from $0.0061min^{-1}$ to $0.0197min^{-1}$ when microwave was additionally irradiated. This study demonstrates that the microwave irradiation can play a very important role in photocatalytic degradation using peroxides although it is not easy to quantitatively assess the effect of microwave on photocatalytic reactions from the experimental data of this study.