• 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 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.

• Geotechnical Engineering
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• v.13 no.6
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• pp.5-12
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• 1997

Predictions of settlements under preloading for the improvement of soft soil is a very important element of construction management. Due to the non uniformity, difficulty of estimating resonable soil properties, predictions of settlements and settlement velocities at the design stage seldom agree with the actual future settlements. To overcome this problem, the prediction methods based on the settlement observation of initial preloading stage such as hyperbolic method and Asaoka method have been employed frequently. However the estimating method for the reliability of these predictions at the time of prediction has not been suggested. In this study, comparisons of predicted settlements by hyperbolic met hed and observed settlements are explored through case studies. And a stratagem of estimating reliability of settlement predictions by hyperbolic method is suggested as the result of investigation on the relationship between the initial observed time and error of settlement prediction by hyperbolic method.

• Journal of the Korean GEO-environmental Society
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• v.13 no.12
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• pp.35-42
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• 2012

There are many large-scale coastal region landfill and land development by loading to use territory efficiently, this regions are mostly soft clay ground. Constructing structures and road on the soft ground bring about engineering problems like ground shear fracture and a big amount of consolidation by bearing capacity. Improvement of soft soil is required to secure soil strength and settlement control. In improvement of soft soil, predict for the amount of settlement based on field surveyed reports are important element for estimating pre-loading banking height and the final point of consolidation. In this study, there is calculating theoretical settlement by analyzing field surveyed report and ground investigation to improvement of soft soil with pre-loading and vertical drain method. And present settlement prediction method reflect soil characteristics in Gimpo Hangang site by analysing prediction settlement and observational settlement during compaction using hyperbolic, ${\sqrt{s}}$, Asaoka method.

• Tunnel and Underground Space
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• v.19 no.5
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• pp.463-472
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• 2009

Many old domestic mines were excavated with the room and pillar method or the sublevel caving method and they involve the great possibility of surface subsidence, especially in the shallow depth mines. In most of these cases, the mine roadways and openings are very irregular in shape and the information about the local geology is uncertain. Consequently it is not simple to standardize the estimation method for the possibility of subsidence, especially the sinkhole subsidence. In this study, the fuzzy reasoning method has been applied for development of estimating the possibility of subsidence occurrence in abandoned mine area. This method has the advantage in producing the reliable estimation results with a simple performance procedure even when the precise information on the local geology and mining conditions is rare. For the verification of applicability of this method, the developed method has been applied to Kumho mine in Bonghwa, Kyungbook province and the Choong-ju mine in Iryu, Choongbook province where the surface subsidence occurred already.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.6
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• pp.914-921
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• 2010

When industrial structures are constructed on soft ground, ground subsidence is occurred by problems of bearing capacity. To protect ground subsidence have to improve soft ground, and have to predict settlement estimation for reasonable construction. Artificial Neural Networks(ANN) is adopted for prediction of settlement of construction during the initial design. In the study, Artificial Neural Networks are applied to predict the settlement estimation of initial condition ground and ground improved by D.C.M method. Also, this study compares results of Artificial Neural Networks and results of continuum analysis using Mohr-Coulomb models. In result, settlements of initial condition ground decreased over 0.7 times. Also, by comparing ANN and continuum analysis, coefficient of determination was comparatively high value 0.79. Thought this study, it was confirmed that settlements of improvement ground is predicted using laboratory experiment data.

• Journal of the Korean GEO-environmental Society
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• v.20 no.10
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• pp.29-38
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• 2019

In stability and settlement management of soft ground, the settlement prediction technology has been continuously developed and used to reduce construction cost and confirm the exact land use time. However, the preexistence prediction methods such as hyperbolic method, Asaoka method and Hoshino method are difficult to predict the settlement accurately at the beginning of consolidation because the accurate settlement prediction is possible only after many measurement periods have passed. It is judged as the reason for estimating the future settlement through the proportionality assumption of the slope which the preexistence prediction method computes from the settlement curve. In this study, ARIMA technique is introduced among time series analysis techniques and compared with preexistence prediction methods. ARIMA method was predictable without any distinction of ground conditions, and the results similar to the existing method are predicted early (final settlement).

• Journal of the Korean GEO-environmental Society
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• v.22 no.8
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• pp.13-19
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• 2021

In the case of construction on soft ground - such as national expressways sponsored by Social Overhead Capital (SOC) - many problems occur due to excessive settlement: therefore, an accurate settlement prediction has a major impact on the selection of improvement methods, project budget and construction period. Most of the settlement prediction methods currently used in projects apply Terzaghi's Theory of One-Dimensional Consolidation which assumes the uniformity of the depth of the soft ground. However, the results of soft ground settlement predictions vary when the target layer is divided into multiple horizontal layers. This study analyzed the change in the consolidation settlement behavior according to the horizontal division of soft ground as well as with different loading height.

• Geotechnical Engineering
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• v.12 no.5
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• pp.103-116
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• 1996

Man-made vibrations from traffic and construction activities are important because they may cause damage to structures. The current literature provides that damages in the urban areas were not caused by direct transmission of vibration, but rather through subsequent settlement caused by soil densification. In this paper. prediction technique of ground borne vibration induced settlement was introduced on the basis of case studies. In situ application technique of the settlement prediction model developed in laboratary was described, and the predicted settlement was compared with the measured settlement from case studies. The settlement from case studies hlatched well with the settlement calculated from the model. The parametric studies of settlement in typical urban site conditions were performed to determine the sensitive parameters and to develop reliable vibration monitoring and interpretation schemes. These demonstrated the potential usefulness of the model for the evaluation and prediction of the vibration induced in-situ settlement of sands.

• 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.