• Journal of Korean Society of Environmental Engineers
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• v.22 no.5
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• pp.919-926
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• 2000

The experiment in this study was conducted as a part of an effort to evaluate filter performance with pilot-filters consisting of one mono-media and two dual-media columns. Particle distribution analysis using a particle counter is more sensitive and better than turbidity analysis in observing particle detachments and a breakthrough. In sand media filters having 1.5 m of available head, caution is needed in the head loss of the late stages of filtration, and for dual-media filters, appropriate media configuration and effluent Quality monitoring should be used for preventing the final breakthrough. Also the time of particle breakthrough in the dual media filter can be deferred by increasing bed depth, and it is necessary to use a filtration aid prior to filtration to prevent breakthrough of these intermediate sized particles in high filtration rate.

• Environmental Engineering Research
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• v.24 no.4
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• pp.690-698
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• 2019

Air pollution has attracted ever-increasing attention because of its substantial influence on air quality and human health. To better understand the characteristics of long-range transported pollution, the single particle chemical composition and size were investigated by the single particle aerosol mass spectrometry in Fuzhou, China from 17th to 22nd January, 2016. The results showed that the haze was mainly caused by the transport of cold air mass under higher wind speed (10 m·s^-1) from the Yangtze River Delta region to Fuzhou. The number concentration elevated from 1,000 to 4,500 #·h^-1, and the composition of mobile source and secondary aerosol increased from 24.3% to 30.9% and from 16.0% to 22.5%, respectively. Then, the haze was eliminated by the clean air mass from the sea as indicated by a sharp decrease of particle number concentration from 4,500 to 1,000 #·h^-1. The composition of secondary aerosol and mobile sources decreased from 29.3% to 23.5% and from 30.9% to 23.1%, respectively. The particles with the size ranging from 0.5 to 1.5 ㎛ were mainly in the accumulation mode. The stationary source, mobile source, and secondary aerosol contributed to over 70% of the potential sources. These results will help to understand the physical and chemical characteristics of long- range transported pollutants.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.1
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• pp.97-109
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• 2007

Vertical distribution and optical properties of atmospheric aerosols above the Korean peninsula are quite important to estimate effects of aerosol on atmospheric environment and regional radiative forcing. For the first time in Korea, vertical microphysical properties of atmospheric aerosol obtained by inversion algorithm were analyzed based on optical data of multi-wavelength Raman lidar system developed by the Advanced Environmental Monitoring Research Center (ADEMRC), Gwangju Institute Science and Technology (GIST). Data collected on 14 June 2004 at Gwangju ($35.10^{\circ}N,\;126.53^{\circ}E$) and 27 May 2005 at Anmyeon island ($36.32^{\circ}N,\;126.19^{\circ}E$) were used as raw optical data for inversion algorithm. Siberian forest fire smoke and local originated haze were observed above and within the height of PBL, respectively on 14 June 2004 according to NOAA/Hysplit backstrajectory analysis. The inversion of lidar optical data resulted in particle effective radii around $0.31{\sim}0.33{\mu}m$, single scattering albedo between $0.964{\sim}0.977$ at 532 nm in PBL and effective radii of $0.27{\mu}m$ and single scattering albedo between $0.923{\sim}0.924$ above PBL. In the case on 27 May 2005, biomass burning from east China was a main source of aerosol plume. The inversion results of the data on 27 May 2005 were found to be particle effective radii between $0.23{\sim}0.24{\mu}m$, single scattering albedo around $0.924{\sim}0.929$ at 532 nm. Additionally, the inversion values were well matched with those of Sun/sky radiometer in measurement period.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.13-24
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• 2014

Satellite remote sensing data have been valuable tool for volcanic ash monitoring. In this study, we present the results of application of satellite remote sensing data for monitoring of volcanic ash for three major volcanic eruption cases (2008 Chait$\acute{e}$n, 2010 Eyjafjallaj$\ddot{o}$kull, and 2011 Shinmoedake volcanoes). Volcanic ash detection products based on the Moderate Resolution Imaging Spectro-radiometer (MODIS) observation data using infrared brightness temperature difference technique were compared to the forward air mass trajectory analysis by the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. There was good correlation between MODIS volcanic ash image and trajectory lines after the volcanic eruptions, which support the feasibility of using the integration of satellite observed and model derived data for volcanic ash forecasting.

• Particle and aerosol research
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• v.5 no.2
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• pp.53-62
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• 2009

In this study, the continuous monitoring of the concentration of PM-10 atmospheric particulate matter using beta ray attenuation method was compared with gravimetric method from September, 2006 to August, 2007. On the effects of the PM-10 concentration and mass difference by relative humidity and precipitation were considered. The result showed that the measurement error between beta ray method and gravimetric method are within -3~6% in average, which means PM-10 concentration data with beta ray method are relatively comparable. The current study also shows that the high PM-10 concentration events are mainly due to haze, Asian dust, and high relative humidity and the PM-10 mass concentration is closely related with relative humidity and precipitation events. Based on daily mean data, the PM-10 increases as relative humidity increases up to 70~80%, then decreases over 80% due to the precipitation. However, the distinct measurement discrepancy was not shown between beta ray method and gravimetric method based on current results. Consequently, this study shows that the collocated measurement in different instrument is essential in order to quantify the accuracy of PM-10. Furthermore, the more comprehensive and spatially distributed comparison is needed and this is remained for future study.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.103-111
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• 2022

Fine dust can cause serious problems to human health, and fugitive dust generated at construction sites is one of the main sources of fine dust in Korea. However, monitoring of the amount of fugitive dust generated at the ready-mixed concrete plant site is not performed, and only passive monitoring methods are partially applied in the field. Since it is impossible to control fugitive dust after it is exposed to the air, it is very important to suppress the occurrence or to remove it immediately at the stage of occurrence. Therefore, after identifying the characteristics through real-time monitoring in the fugitive dust generation stage, systematic management is required for suppressing or removing scattering dust in the field. In this study, the scattering dust generation characteristics were analyzed by measuring the particle mass concentration(PMC) of Fugitive dust generated at the aggregate unloading site of the ready-mixed concrete plant in real-time.

• Korean Chemical Engineering Research
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• v.55 no.2
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• pp.180-189
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• 2017

Pharmaceutical co-crystals primarily to improve the solubility as well as stability of insoluble drug are to be investigated more intensively for IMDs as US FDA has reclassified co-crystal as a special case of solvates in August this year. In this study, we proposed a mechanism of indomethacin-saccharin co-crystal formation and the creation of transient indomethacin meta-stable form using in-line monitoring tools with the addition rate of anti-solvent as a critical process parameter. Among various instruments, we combined PVM (particle vision measurement) and FBRM (focused beam reflectance measurement) for the in-line monitoring of anti-solvent co-crystallization process. The off-line characterization of resulting powders was carried out employing the PXRD (powder x-ray diffraction) and DSC (differential scanning calorimeter). It was observed that the pathway to the final IMC-SAC co-crystal was significantly dependent upon the anti-solvent addition rate. The process conditions to obtain high quality co-crystal powder effectively were established. Consequently, we concluded that in-line monitoring combing the PVM and FBRM should be useful for the in-line monitoring of pharmaceutical co-crystallization processes.

• Smart Structures and Systems
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• v.15 no.2
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• pp.299-314
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• 2015

Submersed rock-berm structures are frequently used for protection of underwater lifelines such as pipelines and power cables. During the service life, the rock-berm structure can experience several accidental loads such as anchor collision. The consequences can be severe with a certain level of frequency; hence, the structural responses should be carefully understood for implementing a proper structural health monitoring method. However, no study has been made to quantify the structural responses because it is hard to deal with the individual behavior of each rock. Therefore, this study presents a collision analysis of the submersed rock-berm structure using a finite element software package by facilitating the smoothed-particle hydrodynamics (SPH) method. The analysis results were compared with those obtained from the Lagrange method. Moreover, two types of anchors (stock anchor and stockless anchor), three collision points and two different drop velocities (terminal velocity of each anchor and 5 m/s) were selected to investigate the changes in the responses. Finally, the effect of these parameters (analysis method, anchor type, collision point and drop velocity) on the analysis results was studied. Accordingly, the effectiveness of the SPH method is verified, a safe rock-berm height (over 1 m) is proposed, and a gauge point (0.5 m above the seabed) is suggested for a structural health monitoring implementation.

• Smart Structures and Systems
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• v.26 no.5
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• pp.591-603
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• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.