• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.104-109
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• 2017

As the ground subsidence occurred at the center of Seoul area in 2014, the ground subsidence phenomenon was emerged as a social issue in Korea. Even so far, national and local governments and related experts have been making a lot of efforts to prevent ground subsidence phenomenon, but it is still happening all over the country. In this study, we chose 9 influence factors on which ground subsidence and derived weights using AHP(Analytic Hierarchy Process) method for ground subsidence risk analysis. And we analyze the risk of subsidence in ${\bigcirc}{\bigcirc}$city using GIS(Geographic Information System) analysis method and evaluate the potential risk.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.1
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• pp.38-47
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• 2011

This study focused on health risk assessment via multi-routes of As exposure to establish a target cleanup level (TCL) in abandoned mines. Soil, ground water, and rice samples were collected near ten abandoned mines in November 2009. The As contaminations measured in all samples were used for determining the probabilistic health risk by Monte-Carlo simulation techniques. The human exposure to As compound was attributed to ground water ingestion. Cancer risk probability (R) via ground water and rice intake exceeded the acceptable risk range of $10^{-6}{\sim}10^{-4}$ in all selected mines. In particular, the MB mine showed the higher R value than other mines. The non-carcinogenic effects, estimated by comparing the average As exposure with corresponding reference dose were determined by hazard quotient (HQ) values, which were less than 1.0 via ground water and rice intake in SD, NS, and MB mines. This implied that the non-carcinogenic toxic effects, due to this exposure pathway had a greater possibility to occur than those in other mines. Besides, hazard index (HI) values, representing overall toxic effects by summed the HQ values were also greater than 1.0 in SD, NS, JA, and IA mines. This revealed that non-carcinogenic toxic effects were generally occurred. The As contaminants in all selected mines exceeded the TCL values for target cancer risk ($10^{-6}$) through ground water ingestion and rice intake. However, the As level in soil was greater than TCL value for target cancer risk via inadvertent soil ingestion pathway, except for KK mine. In TCL values for target hazard quotient (THQ), the As contaminants in soil did not exceed such TCL value. On the contrary, the As levels in ground water and polished rice in SD, NS, IA, and MB mines were also beyond the TCL values via ground water and rice intake. This study concluded that the health risks through ground water and rice intake were greater than those though soil inadvertent ingestion and dermal contact. In addition, it suggests that the abandoned mines to exceed the risk-based TCL values are carefully necessary to monitor for soil remediation.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.10a
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• pp.509-514
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• 2006

Considering the risk management, there are many examples and various studies for the corporation risk. However, I have never seen the project risk management that applied a construction site for practical approach. Therefore, I have developed a chart (I-Chart) for the project risk management, and also built a model (I-Chart scenario analysis) that I could use. I applied this model to container yard reclaimed land in harbor construction with approaching of geotechnical engineering.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.113-118
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• 2009

Grounding systems set the reference voltage level of electric circuits and suppress the Ground Potential Rise (GPR) by flowing fault currents to the ground safely. There are several parameters which evaluate the performance of grounding systems as ground resistance, touch voltage and step voltage. The touch and step voltages, which is called "risk voltage", are especially important to ensure the safety of human body. This paper dealt with the influence of current sources with the different frequency components on the touch and the step voltages. Three types of current sources as commercial frequency, square wave, and surge with the fast risetime of $50\;ns{\sim}500\;ns$ were used to analyze the risk voltages in a grounding system. The risk voltages showed remarkable difference in the same current amplitude depending on the current sources, and increased linearly with the current amplitude in the same current source. From the experimental results, it was confirmed that the risk voltages can be evaluated by a small current application in large-scale grounding systems and the possible largest risk voltage can be calculated by a surge current with the risetime of 200 ns or a current source with the same frequency component as the surge current.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.4
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• pp.214-219
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• 2011

The substation grounding design,"IEEE Guide for Safety in AC Substation Grounding (ANSI / IEEE Std 80)"has been widely used. Substation grounding design and substation grounding resistance of grounding network site to predict the voltage at the risk of a very important task, which is a ground fault current due to the influx of the ground network and due to rise in the Earth's potential can be applied to human dangerous Voltage within safe tolerances be configured to be the ground because the network. IEEE Std. 80 for the substation construction safety equipment on the ground securing the ground electrode and the mesh around the boundary potential distribution in terms of risk analysis by the touch voltage and the reference was to clean up the definition and the basic steps of the voltage of the voltage limits the risk of peripheral grounding electrode Suppression by the simulator through a new secure from dangerous voltage design techniques were presented.

• Earthquakes and Structures
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• v.14 no.6
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• pp.577-587
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• 2018

The quantitative assessment of the seismic collapse risk of a structure requires the usage of an optimal intensity measure (IM) which can adequately characterise the severity of the ground motion. Research suggests that the average spectral acceleration ($Sa_{avg}$) may be an efficient and sufficient alternate IM as compared to the more traditional first mode spectral acceleration, $Sa(T_1)$, particularly during seismic collapse risk estimation. This study primarily presents a comparative evaluation of the sufficiency of the average spectral acceleration with respect to ground motion duration, and secondarily assesses the impact of ground motion duration on collapse risk estimation. By assembling a suite of 100 historical ground motions, incremental dynamic analysis of 60 different inelastic single-degree-of-freedom (SDF) oscillators with varying periods and ductility capacities were analysed, and collapse risk estimates obtained. Linear regression models are used to comparatively quantify the sufficiency of $Sa_{avg}$ and $Sa(T_1)$ using four significant duration metrics. Results suggests that an improved sufficiency may exist for $Sa_{avg}$ when the period of the SDF system increases, particularly beyond 0.5, as compare to $Sa(T_1)$. In reference to the ground motion duration measures, results indicated that the sufficiency of $Sa_{avg}$ is more sensitive to significant duration definitions that consider almost the full wave train of an accelerogram ($SD_{a5-95}$ and $SD_{v5-95}$). In order to obtain a reduced variability of the collapse risk estimate, the 5-95% significant duration metric defined using the Arias integral ($SD_{a5-95}$) should be used for seismic collapse risk estimation in conjunction with $Sa_{avg}$.

• Journal of the Korean Geotechnical Society
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• v.38 no.9
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• pp.69-77
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• 2022

Several studies have been conducted to analyze the risk of ground subsidence occurring in urban areas. Recently, the correlation between the density of underground utilities (i.e., the quantity of buried utilities in the analysis area) and the recorded ground subsidence has been explored to analyze such risk through. Choi et al. (2021) proposed an algorithm to optimize the correlation between the ground subsidence and normalized linear density of underground pipelines. In this study, the optimization algorithm was modified for analysis based on the risk grade. The analysis results using the modified optimization algorithm were compared with the correlation analysis results between the density of underground utilities and recorded ground subsidence presented by Choi et al. (2021). Compared with Choi et al. (2021), three analysis results showed equal or higher accuracy in the correlation analysis with recorded ground subsidence according to risk grade. In particular, for R100, it was divided into five grades and compared with the ratio of the recorded ground subsidence that occurred in grades 4 or higher. As a result, Choi et al. (2021) showed that 86% of recorded ground subsidence occurred in grades 4 or higher, whereas this study showed 93%. It was confirmed that the accuracy of the modified optimization algorithm was improved. The modified optimization algorithm can be applied to develop a ground subsidence risk map for each grade in an urban area, which can be used as basic data for decision-making for underground utility maintenance.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1420-1427
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• 2023

Seismic risk has received increased attention since the 2011 Fukushima accident in Japan. The seismic risk of a nuclear power plant is evaluated via seismic probabilistic safety assessment (PSA), for which several methods are available. Recently, the discrete approach has become widely used. This approximates the seismic risk by discretizing the ground motion level interval into a small number of subintervals with the expectation of providing a conservative result. The present study examines the effect of the number of subintervals upon the results of seismic risk quantification. It is demonstrated that a small number of subintervals may lead to either an underestimation or overestimation of the seismic risk depending on the ground motion level. The present paper also provides a method for finding the boundaries between overestimation and underestimation regions, and illustrates the effect of the number of subintervals upon the seismic risk evaluation with an example. By providing a method for determining the effect of a small number of subintervals upon the results of seismic risk quantification, the present study will assist seismic PSA analysts to determine the appropriate number of subintervals and to better understand seismic risk quantification.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.3099-3103
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• 2011

In measurement of risk voltages; the step and touch voltage, the distance between the current electrode and the ground electrode recedes up to several hundred meters as the scale of grounding system increases. This paper dealt with the measurement method of risk voltage in a restricted space. The risk voltage was analyzed depending on the distance and the direction of the current electrode from the ground electrode in a $10[m]{\times}10[m]$ mesh grounding system. The average value of risk voltages measured at a point 20 [m] away from the current electrode was deviated below 5 [%] from that measured at 100 [m] point. Consequently, the evaluation of risk voltage of a large-scale grounding system buried in a spatially restricted place is available if the current electrode is installed in symmetry to the ground electrode.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.5-10
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• 2022

Ground Subsidence has been continuously occurring in densely populated downtown. The main cause of ground subsidence is the damaged underground facility like sewer. Currently, ground subsidence is being dealt with by discovering cavities in ground using GPR. However, this consumes large amount of manpower and cost, so it is necessary to predict hazardous area for efficient operation of GPR. In this study, ◯◯city is divided into 500 m×500 m grids. Then, data set was constructed using the characteristics of the underground facility and ground subsidence in grids. Data set used to machine learning model for ground subsidence risk grade prediction. The purposed model would be used to present a ground subsidence risk map of target area.