• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.334-343
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• 2023

Purpose: In this study, the cavity data found through ground cavity exploration was combined with underground facilities to derive a correlation, and the ground subsidence prediction map was verified based on the AI algorithm. Method: The study was conducted in three stages. The stage of data investigation and big data collection related to risk assessment. Data pre-processing steps for AI analysis. And it is the step of verifying the ground subsidence risk prediction map using the AI algorithm. Result: By analyzing the ground subsidence risk prediction map prepared, it was possible to confirm the distribution of risk grades in three stages of emergency, priority, and general for Busanjin-gu and Saha-gu. In addition, by arranging the predicted ground subsidence risk ratings for each section of the road route, it was confirmed that 3 out of 61 sections in Busanjin-gu and 7 out of 68 sections in Sahagu included roads with emergency ratings. Conclusion: Based on the verified ground subsidence risk prediction map, it is possible to provide citizens with a safe road environment by setting the exploration section according to the risk level and conducting investigation.

• Tunnel and Underground Space
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• v.15 no.3 s.56
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• pp.195-212
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• 2005

Surface subsidence which occurs with several reasons, such as collapse of gangway, discharge of groundwater, compaction of weak rock mass, and tunnel excavation in shallow depth, gives rise to a serious problem in national infra-structures. In this study, therefore, the mechanism of subsidence has been examined numerically to overcome the passive approach on subsidence occurrence area. With many kinds of numerical studies, the major geotechnical parameters have been selected and the weighted values have been defined for each parameters. Also the authors developed the numerical program which can estimate the possibility of subsidence occurrence, and proposed the decision method for objective and quantitative guideline. It is anticipated that this research will be helpful to establish the hazard map on subsidence region.

• Journal of the Society of Disaster Information
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• v.19 no.2
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• pp.313-325
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• 2023

Purpose: According to the recent occurrence statistics of ground accidents, ground subsidence and subsidence have become social problems as the frequency has increased centering around the downtown areas. This study tried to clarify risk of detailed factors which have an effect on subsidence. Method: For the study, detailed risk factors of 28 foundations were mainly drawn through the materials, precedent studies, and research reports shown by analyzing JIS' accident cases from 2016 to September 6, 2022 and by taking advice from an excavation expert. And risk was assessed by conducting a survey on 12 subsidence experts from the universities, research institutes, and industries and applying Fuzzy-FMEA to it. Result: It has found that damage of sewer pipes is 24.99% of overall risk, followed by excavation work (17.34%), water pipes (14.84%), and poor compaction (refill) (13.93%). And it has found that risk of damaging utilities (water pipes, sewer pipes, and other utilities) is highest, followed by poor construction works (excavation work, damage of sewer and water pipes, and other utility work) and poor compaction (refill). Conclusion: This shows that risk of subsidence factors judged by experts is similar with JIS' cases of ground subsidence.

• Economic and Environmental Geology
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• v.40 no.3 s.184
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• pp.295-306
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• 2007

In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.559-575
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• 2021

Due to the increase in ground excavation work, the possibility of ground subsidence accidents is increasing. And it is very difficult to prevent these risk fundamentally through institutional reinforcement such as the special law for underground safety management. As for the various cases of urban ground excavation practice, the ground subsidence behavior characteristics which is predicted using various information before excavation showed a considerable difference that could not be ignored compared to the results real construction data. Changes in site conditions such as seasonal differences in design and construction period, changes in construction methods depending on the site conditions and long-term construction suspension due to various reasons could be considered as the main causes. As the countermeasures, the safety management system through various construction information is introduced, but there is still no suitable system which can predict the effect of excavation and risk assessment. In this study, a web-based system was developed in order to predict the degree of impact on the ground subsidence and surrounding structures in advance before ground excavation and evaluate the risk in the design and construction of urban ground excavation projects. A system was built using time series analysis technique that can predict the current and future behavior characteristics such as ground water level and settlement based on past field construction records with field monitoring data. It was presented as a geotechnical data visualization (GDV) technology for risk reduction and disaster management based on web-based system, Using this newly developed web-based assessment system, it is possible to predict ground excavation impact prediction and risk assessment.

• 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.

• Journal of the Korean Geosynthetics Society
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• v.17 no.3
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• pp.47-55
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• 2018

Recently, increasing number of urban ground subsidence occurrences has been identified. This situation is mainly due to the increased number of underground cavities. This study is intended to develop the method that prevents ground settlement caused by deteriorated or damaged sewers, which are the main cause of land subsidence. To that end, GPR exploration was conducted using CCTV monitoring of deteriorated sewer at the location with high settlement potential. Through such CCTV monitoring and GPR investigation, abnormal ground behavior was monitored at the site where sewer was damaged, joint was cracked and soil was deposited. According to site investigation in this study, evaluation method using correlation analysis of CCTV monitoring and GPR investigation results is expected to prevent ground settlement attributable to damaged sewer.

• Journal of the Korean GEO-environmental Society
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• v.22 no.7
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• pp.13-20
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• 2021

The problem of subsidence of the roadbed near the Honam High Speed Railway, which opened in April 2015, continues to be raised, and the ground stability of the area near the Honam High Speed Railway may also be problematic. It is very important to select the factors that determine the indicators and indicators in producing the risk maps. Existing risk indicators are calculated as the final displacement volume based on the last observed date of the observed period, and time-series indicator displacement must be identified to analyze the cause of subsidence and the behavior of the indicator. Furthermore, for a wide range of regions, it is economically inefficient to conduct direct level measurements, so we wanted to observe surface displacement using SAR images. In this paper, time series indicator displacement was observed using PS-InSAR techniques, and risk was compared by rating each factor using the difference between final indicator displacement, cumulative indicator displacement, minimum displacement and maximum displacement as factors for determining risk indicators. As a result, the risk rating of the final displacement is different from that of each factor, and we propose adding factors from different perspectives in determining risk indicators. It is expected to be an important study in finding the cause of ground subsidence and finding solutions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1105-1123
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• 2018

The main risk factors of tunnel excavation through urban areas are ground settlement and surface sink which caused by ground conditions, excavation method, groundwater condition, excavation length, support method, etc. In the process of ground settlement assessment, the numerical analysis should be conducted considering the displacement and stress due to tunnel excavation. Therefore a technique that can simplify such process and easily evaluate the influence of tunnel excavation is needed. This study focused on the tunnelling-induced ground settlement which is main consideration of underground safety impact assessment. The parametric numerical analyses were performed considering such parameters as ground conditions, tunnel depth, and lateral distance from tunnel center line, etc. A simplified ground settlement evaluation chart was suggested by analyzing tendency of ground subsidence, lateral influence area and character by depth. The applicability of the suggested settlement evaluation chart was verified by comparative numerical analysis of settlement characteristics.

• Journal of the Korean Geotechnical Society
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• v.33 no.10
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• pp.5-14
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• 2017

The hazard maps for predicting collapse on natural slopes consist of a combination of topographic, hydrological, and geological factors. Topographic factors are extracted from DEM, including aspect, slope, curvature, and topographic index. Hydrological factors, such as soil drainage, stream-power index, and wetness index are most important factors for slope instability. However, most of the urban areas are located on the plains and it is difficult to apply the hazard map using the topography and hydrological factors. In order to evaluate the risk of subsidence of flat and low slope areas, soil depth and groundwater level data were collected and used as a factor for interpretation. In addition, the reliability of the hazard map was compared with the disaster history of the study area (Gangnam-gu and Yeouido district). In the disaster map of the disaster prevention agency, the urban area was mostly classified as the stable area and did not reflect the collapse history. Soil depth, drainage conditions and groundwater level obtained from boreholes were added as input data of hazard map, and disaster vulnerability increased at the location where the actual subsidence points. In the study area where damage occurred, the moderate and low grades of the vulnerability of previous hazard map were 12% and 88%, respectively. While, the improved map showed 2% high grade, moderate grade 29%, low grade 66% and very low grade 2%. These results were similar to actual damage.