• Smart Structures and Systems
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• v.18 no.3
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• pp.525-540
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• 2016

The CFRP-confined circular concrete-filled steel tubular column is composed of concrete, steel, and CFRP. Its failure mechanics are complex. The most important difficulties are lack of an available method to establish a relationship between a specific damage mechanism and its acoustic emission (AE) characteristic parameter. In this study, AE technique was used to monitor the evolution of damage in CFRP-confined circular concrete-filled steel tubular columns. A fuzzy c-means method was developed to determine the relationship between the AE signal and failure mechanisms. Cluster analysis results indicate that the main AE sources include five types: matrix cracking, debonding, fiber fracture, steel buckling, and concrete crushing. This technology can not only totally separate five types of damage sources, but also make it easier to judge the damage evolution process. Furthermore, typical damage waveforms were analyzed through wavelet analysis based on the cluster results, and the damage modes were determined according to the frequency distribution of AE signals.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.233-248
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• 2012

The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.20-21
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• 2009

우리는 전면 발광 소자에서 두께에 따른 발광 스펙트럼을 연구하였다. 소자 구조는 Al(100nm)/TPD(40nm)/Alq3(60nm)/LiF(0.5nm)/Al(2nm)/Ag(30nm)으로 하였다. N,N'-diphenyl-N,N'-di(m-tolyl)-benzidine(TPD)와 tris-(8-hydroxyquinoline) aluminium(Alq3)는 전공 수송층과 발광층으로 각각 사용되었다. 반투명 전극은 Li/Al/Ag로 하였다. 유기물층과 전극은 $2\times10-5$torr의 진공도에서 열 증착하였다. 유기물과 금속의 증착 속도는 $0.5\sim1.0{\AA}/s$과 $0.5\sim5{\AA}/s$로 하였다. 제작된 소자는 두께가 증가할 수록 장파장으로 이동하는 현상을 보였다. 이러한 현상은 마이크로 캐비티 이론으로 설명할 수 있다. 소자는 이론적인 마이크로 캐비티 수식을 이용하여 분석하기 위해 각각의 변수를 이용하여 실험과 이론을 비교하였을 때, 각각의 스펙트럼이 거의 일치하는 것을 확인할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.863-868
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• 2004

Reheating furnace is an essential facility of a rod mill plant where a billet is heated to the required rolling temperature so that it can be milled to produce wire. Sometimes, it is also necessary to control a transient billet temperature pattern according to the material characteristics to prevent a wire from breaking. Though it is very important objective to obtain a correct information of a billet temperature during furnace operation. Consequently, a billet temperature profile must be estimated. In this paper, a billet heat transfer model based on FEM (Finite Element Method) with spatially distributed emission factors is proposed and a measurement is also carried out for two different furnace operation conditions. Finally, the difference between the model outputs and the measurements is minimized by using the new optimization algorithm named uDEAS(Univariate Dynamic Encoding Algorithm for Searches) with multi-step tuning strategy. Hence, the information of billet temperatures can be obtained by using proposed model on various furnace operation conditions.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.3
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• pp.170-174
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• 1994

Atmospheric lead concentrations in Seoul were monitored for ten years from January 1984 to June 1993 using X-ray fluorescence Spectrometer. 342 aerosol samples were collected using high volume samplers at two sites : one at Chungang University campus from 1984 to 1988 and the other at Yonsei University campus from 1989 to 1993. Lead concentration increased steadily from about 300ng/㎥ to the maximum of about 600ng/㎥ in 1988 and then decreased, and this is similar to the pattern of Korean leaded gasoline sales implying that Korean automobile emission is the main source. However, the emission from nation's coal combustion appeared to be substantial as welt, and this emmision is the major cause for the secondary feature strong seasonal variability. Lead concentration varied systematically from season to season, low in summer and high in winter. The region's characteristic climate, frequent and heavy precipitations in summer and dry in winter is considered to be another cause for the seasonal variability.

• 한국연소학회:학술대회논문집
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• 2012.11a
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• pp.221-223
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• 2012

Since gas turbine using biogas can reduce carbon dioxide ($CO_2$), the biogas gas turbine is becoming more attractive to renewable energy utilization business sector. Natural gas and $CO_2$ mixture was used to simulate the biogas fuel. At the experiments pressure losses, pattern factor, and emissions were measured. The results revealed that methane concentrations of the fuel mixture showed little effects on the combustor performance except emissions. As methane concentrations in fuel decreased, emissions measured at the exit of the combustor decreased.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.848-850
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• 2001

In this work, we investigated on the white-colored ribbon fiber synthesized from GaN powder. We convinced the formation of monoclinic phase $\beta$-Ga$_2$O$_3$from the X-ray diffraction pattern on ribbon fiber. The 10 K PL spectrum consisted with the strong emission band caused by self-activated optical center at 3.464 eV with the full-width at half maximum of 48 meV and the impurity related emission bands. Through this work, the optical properties and the electrical conductivity of $\beta$-Ga$_2$O$_3$, it will be useful for the fabrication of optoelctronic devices operating in visible spectrum region.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.499-502
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• 2008

Effects of a dielectric capping layer on the luminous characteristics of top emitting organic light emitting diodes (TOLEDs) have been analyzed using a classical electromagnetic theory. Special attention was given to the influence of the cavity length on the effectiveness of the capping layer. The luminance characteristics of the TOLEDs influenced by the combined effects of the cavity length and the capping layer thickness. Furthermore, these combined effects also modify the emission spectrum and pattern of the TOLEDs, which result in the improvement of total luminance of the device, but no significant change in the device out-coupling efficiency.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.259-262
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• 1997

In this paper, a fuzzy model based on the polynomial Neural Network(PNN) structure is proposed to estimate the emission pattern for air pollutant in power plants. The new algorithm uses PNN algorithm based on Group Method of Data Handling (GMDH) algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the least square method in order to identify the optimal consequence parameters. Both time series data for the gas furnace and data for the NOx emission process of gas turbine power plants are used for the purpose of evaluating the performance of the fuzzy model. The simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy anhd feasibility than other works achieved previously.