• 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.

• 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.13 no.4
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• pp.77-91
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• 2012

Recently, construction of housing sites, complexes, roads, ports and airports is increasing for high-intensity use of the country and balanced development between regions. Presently, constructions are being conducted at soft ground. Consequently, engineering problems as long-term settlement of the ground, differential settlement, local structural damage have been reported consistently at construction site. In particular, long-term subsidence of the ground as various constructions and loads by the load will necessarily occur in the soft ground of west-south coast and inland coast. Therefore, in this study, regional proper analysis methods of the Hyperbole method, Hosino method, $\sqrt{S}$ method, Asaoka method etc as existing long-term settlement prediction methods have been examined and a study on new prediction method was conducted through deduction of a generalized equation. Correlation coefficients of soil properties and construction conditions has been analyzed and a matching coefficient of long-term settlement characteristics has been deducted. Comparison and analysis of monitoring data and numerical analysis results of 16 local area have been conducted.

• 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.18 no.5
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• pp.355-365
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• 2008

Displacement caused by tunneling is difficult to predict since it is affected by many factors such as ground condition, excavation method and supplementary method of reinforcement. In this study, horizontal inclinometer was employed to monitor ground settlements above a tunnel face before and after the excavation. Monitoring results were analyzed to predict the preceding displacement and settlement of the surface structures. The result of the analysis can be used to establish a proper counter measure which keeps the serviceability of the surface structures. Based on the analysis of the monitoring result, ground properties of the site were deduced and the influence of the tunnel excavation on the settlement of the foundation above the tunnel is analyzed.

• Journal of the Korean Geotechnical Society
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• v.20 no.8
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• pp.29-39
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• 2004

The prediction of landfill settlement is very important for managing land properly, especially in small national land like Korea. It is difficult to express settlement using the consolidation theory because biochemical decomposition is main reason of settlement, and organic materials in landfill are decomposed far long time. In this study, LFG (Landfill Gas) generation characteristics are studied to find long-term settlement analysing model landfills. Two lysimeters are made; one is leachate recycled, and the other is not leachate recycled. The relationship between gas generation and settlement is analysed as a function of time. A mathematical gas generation model is suggested to predict long-term settlement due to biodegradation, and correction coefficient is recommended for long term settlement through model tests. The leachate recirculation system is more effective to accelerate landfill settlement. The appropriate coefficients of gas correction for non-recycled leachate model are 1.4 and 1.7 for recycled system from tests showing 22% of acceleration.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.21-28
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• 2018

Despite a number of studies on consolidation behavior that have been carried out in the Nakdong River estuary in Busan, these are focused on the prediction of final settlement during ground improvement process, and there is almost no research on the long-term settlement occurring after that. For the practical study on the long-term settlement, the field monitored settlement data that measured over 10 years in the Busan new port facilities area were used, and the final settlement and predicted time-settlement line were constituted by hyperbolic function. As a result, the measured settlements depend on the thickness of clayey soils, and the pattern were similar to each other and good agreement with the predicted time-settlement line using hyperbolic method. Also, the settlement in the lower non-improved layer occupied 62-76% of total settlement. Information about above results would be quite helpful to understand the long-term settlement behaviors as well as the non-improved layer's settlement is more careful consideration needed at design phase.

• Journal of the Korean Geotechnical Society
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• v.18 no.3
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• pp.113-125
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• 2002

Although there are several empirical and semi-empirical formulae available for predicting ground surface settlement, most of them do not simultaneously take into consideration all the relevant factors, resulting in inaccurate predictions. In this study, an artificial neural network (ANN) is incorporated with 113 of monitored field results to predict surface settlement for a tunnel site with prescribed conditions. To achieve this, a format for a database of monitored field data is first proposed and then used for sorting out a variety of monitored data sets available in Korea Institute of Construction Technology. An optimal neural network model is suggested through preliminary parametric studies and introduces a concept of RSE (Yang and Zhang, 1997) in sensitivity analysis for various major factors affecting the surface settlement in tunnelling. It is seen in some examples that the RSE rationally enables to recognize the most significant factors of all the contributing factors. Two verification examples are undertaken with the trained ANN using the database created in this study. It is shown from the examples that the ANN has adequately recognized the characteristics of the monitored data sets retaining a generality fur further prediction.

• Journal of the Korean Geotechnical Society
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• v.19 no.3
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• pp.39-44
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• 2003

Centrifuge test was conducted to simulate the effects of consolidation settlement of capped contaminated marine sediment. A fluorescent dye was used to monitor the movement of pore water through the cap layer. Dye tracer study clearly showed the consolidation induced advective transport of contaminants. Thus, the capping layer must be appropriately designed to reduce the effects of consolidation induced advective transport. The results from the centrifuge test were compared to predictions made by the Primary consolidation, Secondary compression, and Desiccation of Dredged Fill (PSDDF) computer program, which can qualitatively estimate the consolidation settlement of capped marine sediment. Although PSDDF approximated closely the secondary compression in the centrifuge test (i.e., compare data points from 18 to 25 prototype years), the maximum deviation between centrifuge test result and PSDDF prediction was 20 % about prototype time 6 years. Thus, designers should utilize PSDDF consolidation settlement results with caution.

• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.4
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• pp.329-340
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• 2010

Mechanical behavior of underground cavity construction such as tunnel is very difficult to estimate due to complexity and uncertainty of ground. Prediction of behavior according to excavation of tunnel mainly uses method utilized of model test or numerical analysis. But scale model test is difficult to reappear field condition, numerical analysis is also very hard to seek choice of suitable constituent model and input data. To solve this problem, this paper forecasted the deformation of tunnel that applied to information of crown settlement and convergence, RMR in weathered granite by using the regression analysis. The result of the analysis shows that the crown settlement according to excavation occurs approximately 70~80% of total displacements within about 20 days. As a result of the prediction of crown settlement and convergence, an exponential function becomes more accurate at measurements than an algebraic function. Also this paper got a correlation in comparison of RMR and displacements of 6 sections.