• Tunnel and Underground Space
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• v.14 no.6 s.53
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• pp.399-410
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• 2004

The utilization of AS(Artificial Intelligence) and Database could be considered as an useful access for the application of underground information from the point of a geotechnical methodology. Its detailed usage has been recently studied in many fields of geo-sciences. In this paper, the target of usage is on controlling the injection of grout which more scientific access is needed in the grouting that has been used a major method in many engineering application. As the proposals for this problem it is suggested the methodology consisting of a fuzzy-neural hybrid system and a database. The database was firstly constructed for parameters dynamically varied according to the conditions of rock mass during the injection of grout. And then the conceptional model for the fuzzy-neural hybrid system was investigated fer optimally finding the controlling range of the grout valve. The investigated model applied to four cases, and it is found that the controlling range of the grout valve was reasonably deduced corresponding to the mechanical phenomena occurred by the injection of grout. Consequently, the algorithm organizing the fuzzy-neural hybrid system and the database as a system can be considered as a tool for controlling the injection condition of grout.

• The Journal of Engineering Geology
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• v.24 no.3
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• pp.343-351
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• 2014

Tunnel face mapping plays an important role in risk analysis and infrastructure support decisions during tunnel construction. In this study, a digital mapping system using a mobile device is employed instead of existing face-mapping methods that rely upon face mapping sheets. The mobile device is then connected to the main server in the field, where a tunnel-specific database is compiled automatically. This information provides real-time feedback on the tunnel face to construction personnel and engineers, thus allowing for rapid assessment of tunnel face stability and infrastructure needs. The Douglas-Peucker algorithm, among others, is employed to resolve problems arising from the detailed mapping and speed problem by data accumulation. This system is expected to raise program optimization through field verification and additional functional improvements.

• 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 GEO-environmental Society
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• v.20 no.3
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• pp.39-46
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• 2019

The liquefaction is a phenomenon that the effective stress becomes zero due to the rapidly accumulated excess pore water pressure when a strong load acts on the ground for a short period of time, such as an earthquake or pile driving, resulting in the loss of the shear strength of the ground. Since the Geongju and Pohang earthquake, liquefaction brought increasing domestic attention. This liquefaction can be assessed mainly through the semi-empirical procedures proposed by Seed and Idriss (1982) and the liquefaction risk based on the penetration resistance obtained from borehole DB and SPT. However, the geotechnical information data obtained by the in-situ tests or boring information fundamentally have an issue of the representative of the target area. Therefore, this study sought to construct a ground information database by classifying and reviewing the ground information required for liquefaction assessment, and tried to solve the representative problem of the soil layer that is subject to liquefaction evaluation by performing spatial interpolation using GIS.

• Journal of the Korean Geotechnical Society
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• v.38 no.8
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• pp.53-66
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• 2022

The national ground survey database (GeoInfo) distributes numerous ground survey data nationwide. Many standard penetration test results exist in this database; however, the number of shear wave velocity (V_S) data is small. Hence, to use abundant standard penetration test-N values to predict V_S, this study proposed a new empirical N-V_S relationship model using GeoInfo data. The proposed N-V_S model is a single equation regardless of geological layer types; the layer type only specifies the upper limit of V_S. To validate the proposed model, residual analysis was performed using a test dataset that was not used for the model development. Therefore, this study's proposed model performed better than N-V_S models from previous studies. Since the N-V_S model in this study was developed using sufficient data from GeoInfo, we expect that it is the most applicable to GeoInfo dataset for V_S prediction.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.155-167
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• 2024

In Korea, many solar power generation facilities are being installed in mountainous regions, which cover 70% of the country' area. This study aimed to analyze the slope characteristics of solar power generation facilities installed in such regions, considering the potential for mountain hazards. A database was created for 663 mountainous solar power generation facilities in Gangwon province, including data on area, slope angle, slope direction, altitude, and soil depth. GIS techniques were used to analyze the slope characteristics of these facilities. The area of solar power generation facilities installed in the Gangwon Mountains ranges from 606 to 320,718 m². We found that a notable number of these facilities have slopes exceeding the permit standards for mountain solar power installations and steep slope criteria. In addition, most facilities are located south, making them vulnerable to landslides. The correlation between soil depth and slope or topographical altitude was found to be quite low.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.17-35
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• 2016

Earthquake-induced disasters are often more severe in locations with soft soils than firm soils or rocks due to differences in ground motion amplification. On a regional scale, such differences can be estimated by spatially predicting subsurface soil thickness over the entire target area. In general, soil deposits are generally deeper in coastal or riverside areas than in inland regions. In this study, a coastal metropolitan area, Incheon, was selected to assess site effects and provide information on seismic hazards. Spatial prediction of geotechnical layers was performed for the entire study area within the GIS framework. Approximately 7,000 existing borehole drilling data in the Incheon area were gathered and archived into the GIS Database (DB). In addition, surface geotechnical data were acquired from a walkover survey. Based on the built geotechnical DB, spatial zoning maps of site-specific seismic response parameters were created and presented for use in a regional seismic strategy. Site response parameters were performed to determine site coefficients for seismic design over the entire target area and compared with each other. Site classifications and subsequent seismic zoning were assigned based on site coefficients. From this seismic zonation case study in Incheon, we verified that geotechnical GIS-DB can create spatial zoning maps of site-specific seismic response parameters that are useful for seismic hazard mitigation particularly in coastal metropolitan areas.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.170-180
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• 2008

Successful design, construction and maintenance of NATM tunnel demands prediction, control, stability guidelines, the estimation pre-improvement support system and monitoring of surface settlement, gradient and ground displacement with high accuracy. Moreover, urban NATM tunnel under difficult geotechnical conditions is important the estimation and necessary of pre-improvement support system. Various strategies have been proposed for the quantitative estimation of pre-improvement support system. This paper was investigated and analysed an assessment technique for the quantitative estimation of pre-improvement support system on underground space, as mountain and urban tunnel, in detail. The analysis performed on design and construction stage with field database using the proposed stability estimation index by many researcher including the critical strain and the apparent Young's modulus concept.

• Journal of the Korean Geotechnical Society
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• v.23 no.9
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• pp.51-63
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• 2007

Behavior of rock-socketed drilled shafts subjected to axial load was investigated on the basis of pile load tests. The emphasis was laid on analyzing the shear load transfer characteristics from the shafts to surrounding rock. Field load tests were performed on nine test shafts under various conditions such as weathering of rock mass, borehole roughness, pile diameters, and loading directions. The borehole roughness at each test site was profiled using a laser borehole profiler. In order to evaluate and to propose ultimate shaft resistance($f_{max}$) of drilled shafts in rock of Korean peninsular, also, database of pile load tests was developed by reviewing various literature and technical reports.

• Earthquakes and Structures
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• v.7 no.4
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• pp.485-510
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• 2014

In performance-based seismic design procedures Peak Ground Acceleration (PGA) and pseudo-Spectral acceleration ($S_a$) are commonly used to predict the response of structures to earthquake. Recently, research has been carried out to evaluate the predictive capability of these standard Intensity Measures (IMs) with respect to different types of structures and Engineering Demand Parameter (EDP) commonly used to measure damage. Efforts have been also spent to propose alternative IMs that are able to improve the results of the response predictions. However, most of these IMs are not usually employed in probabilistic seismic demand analyses because of the lack of reliable Ground Motion Prediction Equations (GMPEs). In order to define seismic hazard and thus to calculate demand hazard curves it is essential, in fact, to establish a GMPE for the earthquake intensity. In the light of this need, new GMPEs are proposed here for the elastic input energy spectra, energy-based intensity measures that have been shown to be good predictors of both structural and non-structural damage for many types of structures. The proposed GMPEs are developed using mixed-effects models by empirical regressions on a large number of strong-motions selected from the NGA database. Parametric analyses are carried out to show the effect of some properties variation, such as fault mechanism, type of soil, earthquake magnitude and distance, on the considered IMs. Results of comparisons between the proposed GMPEs and other from the literature are finally shown.