• 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.

• The Journal of Engineering Geology
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• v.29 no.3
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• pp.289-302
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• 2019

As the occurrence of ground subsidence near the excavation site increases recently, studies are being conducted to predict the possibility of ground subsidence prior to excavation. In this study, the ground subsidence risk rating for pre-excavation (GSRp) developed by the previous study was applied to actual excavation sites to verify its applicability. The final results for the evaluation of the ground subsidence risk level for five excavation sites revealed that GSRp scores were calculated between 40 and 79 points and classified mainly into grades II (Good Ground)~III (Fair Ground). In order to verify the evaluation method, the obtained GSRp grades were compared with the measured horizontal displacements. The horizontal displacements measured in five excavation sites were between 25% and 47% of the allowable displacement, which were well agreed with the low subsidence risk level obtained from GSRp calculation. It is expected that the GSRp method can be used as an evaluation tool for predicting the risk of ground subsidence before excavation if GSRp is verified and supplemented through the additional research for the poor soil with the high risk of ground subsidence.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.553-563
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• 2018

The recent increase of ground subsidence in Korea requires the development of technology for predicting the possibility of ground subsidence. Eighteen parameters affecting the ground subsidence for pre-excavation are classified into 6 categories considering ground types, groundwater, and external factors. Eighteen parameters consists of a table which gives ground subsidence risk ratings for pre-excavation(GSRp). Certain scores are given to these parameters after they are divided into several classes considering the importance and the credibility of parameters and the engineering judgements of the authors. Because of the difference of ground subsidence factors depending on the ground and field conditions, weighting factors for the individual factor and for the each category are multiplied. Weighting factors are calculated from citation frequencies of influencing factors. Ground subsidence risk ratings for pre-excavation can be quantified by considering the individual score of each parameter and weighting factors for the individual factor and for the each category. The suggested GSRp tables obtained from this study are expected to be used by engineers for the estimation of ground subsidence risk ratings for pre-excavation sites.

• Journal of the Korean Geotechnical Society
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• v.37 no.12
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• pp.117-125
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• 2021

The occurrence of ground subsidence and sinkhole in downtown areas, which threatens the safety of citizens, has been frequently reported. Among the various mechanisms of a sinkhole, soil erosion through the damaged part of the sewer pipe was found to be the main cause in Seoul. In this study, a random forest model for predicting the occurrence of sinkholes caused by damaged sewer pipes based on sewage pipe information was trained using the information on the sewage pipe and the locations of the sinkhole occurrence case in Seoul. The random forest model showed excellent performance in the prediction of sinkhole occurrence after the optimization of its hyperparameters. In addition, it was confirmed that the sewage pipe length, elevation above sea level, slope, depth of landfill, and the risk of ground subsidence were affected in the order of sewage pipe information used as input variables. The results of this study are expected to be used as basic data for the preparation of a sinkhole susceptibility map and the establishment of an underground cavity exploration plan and a sewage pipe maintenance plan.

• Journal of the Korean GEO-environmental Society
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• v.22 no.11
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• pp.23-29
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• 2021

Recently, ground subsidence has been steadily occurring mainly in downtown areas, threatening the safety of citizens. Under the road, various underground facilities such as water supply pipe, sewage pipe, and communication pipe are buried. Due to the aging of these underground facilities and the reckless development of the underground, it is acting as a cause of ground subsidence. Although there is a result of analyzing the risk of ground subsidence according to the deterioration of the existing pipeline, there is no result of analyzing the risk of ground subsidence using the density of pipelines indicating ground disturbance. Therefore, in this study, the density of the underground space was analyzed using the data of six types of representative underground pipelines in Seoul, and a study was conducted on whether there is a correlation with the ground subsidence. As a result, it was found that the density of underground facilities is high in the area where the ground subsidence occurred, indicating that the density of pipelines have an effect on the ground subsidence.

• Journal of the Korean GEO-environmental Society
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• v.22 no.12
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• pp.33-40
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• 2021

The deterioration of underground facilities, disturbance of the ground due to underground development activities, and changes in ground water can cause ground subsidence accidents in the urban areas. The investigation on the geotechnical and hydraulic factors affecting the ground subsidence accident is very significant to predict the ground subsidence risk in advance. In this study, an analysis DB was constructed through 3D ground modeling to utilize the currently operating geotechnical survey information DB and ground water behavior information for risk prediction. Additionally, using these results, the relationship between the actual ground subsidence occurrence history and ground conditions and ground water level changes was confirmed. Furthermore, the methodology used to visualize the risk of ground subsidence was presented by reconstructing the engineering characteristics of the soil presented according to the Unified Soil Classification System (USCS) in the existing geotechnical survey information into the internal erosion sensitivity of the soil, Based on the result, it was confirmed that the ground in the area where the ground subsidence occurred consists of more than 40% of sand (SM, SC, SP, SW) vulnerable to internal erosion. In addition, the effect of the occurrence frequency of ground subsidence due to the change in ground water level is also confirmed.

• Tunnel and Underground Space
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• v.30 no.2
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• pp.149-163
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• 2020

This paper presents a logistic regression and GIS based urban ground sink susceptibility assessment using underground facility information considering soil particle loss. In the underground environment, the particle loss due to water flow or groundwater level change leads to the occurrence and expansion of cavities, which directly affect the ground sink. Four different contributory factors were selected according to the two underground facility domains (water pipeline area, sewer pipeline area) and subway line area. The logistic regression method was used to analyze the correlation and to derive the regression equation between the ground sink inventory and the contributory factors. Based on these results, three ground sink susceptibility maps were generated. The results obtained from this study are expected to provide basic data on the area susceptible to ground sink and needed to safety monitoring.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.399-408
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• 2018

Purpose: Recently, the ground subsidence has caused social problem, because it occurred life and economic damage. Method: Ground subsidence is different from a sink hole. Ground subsidence occurred cavities from loss of by groundwater flow, surface layer is collapsed due to relaxation and expansion. Results: According to the survey, the caused of ground subsidence are classified as ground cavities, surrounding ground relaxation and pipe joint failure. Conclution: Cavities of ground is mainly caused by cavities formed by rainfall induced infiltration of the heavy rainfall, loss of soil due to rise and fall of ground water level and repeated sewage runoff.

• Journal of Korean Society of Disaster and Security
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• v.10 no.1
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• pp.43-46
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• 2017

Recently, the development of underground space is being actively carried out in the urban area by saturation, and the excavation works are mainly carried out by various excavation methods by the structures adjacent to the ground and underground excavation. During such excavation work, ground subsidence accidents are occurring due to inattention construction, lack of construction technology, and leakage of ground water. For the prevention of ground subsidence we studied the method of risk influence factors by soil investigation. Analysis of 75 sites soil investigation by U.S.C.S (Unified Soil Classification System), construction method, depth of excavation and we studied the risk influence factors with ground subsidence.

• Journal of the Korean GEO-environmental Society
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• v.20 no.9
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• pp.5-11
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• 2019

Recently, ground collapse in urban area has been widely paid attention as it frequently happens. To investigate the causes and suggest the measurements, many researches such as ground exploration from GPR, mock test and numerical simulations have been conducted. The proposed risk evaluation chart recently focuses only on the current ground status and is not capable of forecasting the ground collapse. This paper presents the prediction method of ground collapse using the numerical simulations of 30 cases considering void size and ground height as variables. It finally provides the charts that can analyze quantitatively the ground collapse.