• Tunnel and Underground Space
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• v.17 no.5
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• pp.372-380
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• 2007

Surface damage due to subsidence is an inevitable consequence of underground mining, which may be immediate or delayed for many years. The surface damage due to abandoned underground mine is observed to be two subsidence types such as simple sinkhole or trough formation to a large scale sliding of the ground from with in the subsided area. An evaluation of the risk of a subsidence occurrence is vital in the areas affected by mining subsidence. For a subsidence prediction or a risk evaluation, there has been used various methods using empirical models, profile functions, influence functions and numerical models. In this study, a simple but efficient evaluation method of subsidence hazard is suggested, which is based on a diffusion theory and uses just information about geometry of caving and topography. The diffusion model has an analogous relationship with granular model which can explain a mechanism of subsidence. The diffusion model is applied for the evaluation of subsidence hazard in abandoned metal and coal mines. The model is found to be a simple but efficient tool because it needs information of geometry of caving and gangway and the topography.

• Tunnel and Underground Space
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• v.18 no.4
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• pp.272-279
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• 2008

This paper describes the development of a simple and quantitative subsidence hazard estimation method appropriate to Korean coal mines using gangway depth information only. In spite of simpleness of estimation method, this new method gives good results close to those obtained using influence function method when applying to a virtual rectangular excavation model and to a closed mine where actual subsidence occurred. Therefore, this method can be effectively applied to the identification of zones liable to subsidence over closed coal mine in Korea where the shape of extraction is very complex and usually unknown.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.296-300
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• 2007

본 연구에서는 강원도 정선지역 및 삼척지역의 폐탄광 지역에서 관측된 지반침하지역의 공간자료와 각종 지반침하 관련요인을 분석하여, 지질학적구조와 지역적 특성이 상이한 지역에서 지반침하에 직접적인 영향을 주는 공통요인을 찾아내고자 하였다. 연구지역의 지반침하 관련요인들에 대해 GIS(Geographic Information System)를 이용하여 래스터 데이터베이스를 구축하고 모든 요인을 이용하여 분석한 위험지역과 하나의 요인씩 제거하며 분석한 위험지역을 비교하는 민감도 분석 (Sensitivity analysis)을 통해 지반침하와 연관성이 높은 요인을 추출하였다. 민감도 분석은 서로 다른 두 지역에 대해 수행하여 그 결과를 비교하였으며, 갱으로부터의 수평거리，RMR(Rock Mass Rating), 지하수 심도가 지반침하에 영향을 주는 공통요인으로 분석되었다. 본 연구결과, 폐탄광지역의 지반침하에 공통적으로 영향을 끼치는 주 요인을 구할 수 있었으며, 타 지역에서 지반침하 예측시 기존 연구에서 사용한 요인들의 데이터를 전부 구하지 못하는 경우에도 최소한의 필요한 요인을 정할 수 있으며 지반침하 예측의 효율성을 높일 수 있을 것이라 기대된다.

• 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.

• 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.

• 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.

• 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.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2007.03a
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• pp.394-405
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• 2007

• 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.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.