• Proceedings of the KSRS Conference
• /
• 2007.03a
• /
• pp.296-300
• /
• 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
• /
• v.19 no.2
• /
• pp.313-325
• /
• 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.

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

• Journal of the Society of Disaster Information
• /
• v.19 no.2
• /
• pp.334-343
• /
• 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
• /
• v.15 no.3 s.56
• /
• pp.195-212
• /
• 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 Korean Tunnelling and Underground Space Association
• /
• v.23 no.6
• /
• pp.559-575
• /
• 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.

• Proceedings of the KSEEG Conference
• /
• 2007.04a
• /
• pp.205-207
• /
• 2007

• Economic and Environmental Geology
• /
• v.40 no.3 s.184
• /
• pp.295-306
• /
• 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 the Korean GEO-environmental Society
• /
• v.20 no.9
• /
• pp.5-11
• /
• 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.

• Proceedings of the KSRS Conference
• /
• 2007.03a
• /
• pp.301-304
• /
• 2007

본 연구에서는 폐탄광 지역에서 발생하는 지반침하에 영향을 주는 주요 요인들을 추출하기 위하여 다변량 통계분석 방법의 하나인 주성분분석(Principle Component Analysis : PCA)기법과 지리정보시스템 (Geographic Information System : GIS)을 이용하였다. 이를 위해 연구지역에서 수행한 지표지질조사， 정밀조사, 실내암석시험 등으로부터 취득된 자료를 데이터베이스로 구축하고, 지반침하 위험지역 분포를 공간적으로 해석할 수 있는 지질, 토지이용, 경사도， 지표로부터 지하 갱도까지의 심도, 갱도의 지표상 위치로부터의 수평거리, 지하수심도, 투수계수, RMR(Rock Mass Rating) 값을 분석대상으로 선정하였다. 각 요인들이 연구지역 전체에 걸쳐 분포하도록 GIS의 공간분석 기법의 하나인 표면분석(Surface Analysis), 버퍼링기법(Buffering) 및 내삽법(Interpolation)을 이용하여 래스터 데이터베이스로 구축하고 이로부터 추출된 자료들을 입력값으로 하는 주성분분석을 수행하였다. 주성분분석 결과 폐탄광 지역의 지반침하에 영향을 주는 주요인을 추출하는 것이 가능하였으며, 연구지역은 지질 및 지반강도 관련 요인이 침하발생의 가장 큰 요인인 것으로 분석되었다.