• Title/Summary/Keyword: geotechnical application

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Application into Assessment of Liquefaction Hazard and Geotechnical Vulnerability During Earthquake with High-Precision Spatial-Ground Model for a City Development Area (도시개발 영역 고정밀 공간지반모델의 지진 시 액상화 재해 및 지반 취약성 평가 활용)

  • Kim, Han-Saem;Sun, Chang-Guk;Ha, Ik-Soo
    • Journal of the Earthquake Engineering Society of Korea
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    • v.27 no.5
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    • pp.221-230
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    • 2023
  • This study proposes a methodology for assessing seismic liquefaction hazard by implementing high-resolution three-dimensional (3D) ground models with high-density/high-precision site investigation data acquired in an area of interest, which would be linked to geotechnical numerical analysis tools. It is possible to estimate the vulnerability of earthquake-induced geotechnical phenomena (ground motion amplification, liquefaction, landslide, etc.) and their triggering complex disasters across an area for urban development with several stages of high-density datasets. In this study, the spatial-ground models for city development were built with a 3D high-precision grid of 5 m × 5 m × 1 m by applying geostatistic methods. Finally, after comparing each prediction error, the geotechnical model from the Gaussian sequential simulation is selected to assess earthquake-induced geotechnical hazards. In particular, with seven independent input earthquake motions, liquefaction analysis with finite element analyses and hazard mappings with LPI and LSN are performed reliably based on the spatial geotechnical models in the study area. Furthermore, various phenomena and parameters, including settlement in the city planning area, are assessed in terms of geotechnical vulnerability also based on the high-resolution spatial-ground modeling. This case study on the high-precision 3D ground model-based zonations in the area of interest verifies the usefulness in assessing spatially earthquake-induced hazards and geotechnical vulnerability and their decision-making support.

Application of Artificial Neural Networks(ANN) to Ultrasonically Enhanced Soil Flushing of Contaminated Soils (초음파-토양수세법을 이용한 오염지반 복원률증대에 인공신경망의 적용)

  • 황명기;김지형;김영욱
    • Journal of the Korean Geotechnical Society
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    • v.19 no.6
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    • pp.343-350
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    • 2003
  • The range of applications of artificial neural networks(Am) in many branches of geotechnical engineering is growing rapidly. This study was undertaken to develop an analysis model representing ultrasonically enhanced soil flushing by the use of ANN. Input data for the model-development were obtained by laboratory study, and used for training and verification. Analyses involved various ranges of momentum, loaming rate, activation function, hidden layer, and nodes. Results of the analyses were used to obtain the optimum conditions for establishing and verifying the model. The coefficient of correlation between the measured and the predicted data using the developed model was relatively high. It shows potential application of ANN to ultrasonically enhanced soil flushing which is not easy to build up a mathematical model.

Application of Evidence Theory for the Evaluation of Mechanical Rock Mass Properties (암반설계정수 산정을 위한 증거이론의 적용)

  • Jung, Yong-Bok;Kim, Tae-Heok;Choi, Yong-Kun;SunWoo, Choon
    • Proceedings of the Korean Geotechical Society Conference
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    • 2005.03a
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    • pp.521-528
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    • 2005
  • The evaluation process of rock mass properties intrinsically contains some uncertainty due to the inhomogeneity of rock mass and the measurement error. Although various empirical methods for the determination of rock mass properties were suggested, there is no way of integrating various information on rock mass properties except averaging. For these reasons, this research introduces evidence theory which can model epistemic uncertainty and yield reasonable rock mass properties through combining various information such as empirical equations, in-situ test results, and so on. Through the application of evidence theory to the real site investigation and in situ experiment results, an interval of deformation modulus, cohesion and friction angle of rock mass were obtained. The ratios between lower and upper bound of those properties ranges from 1.6 to 3.6. Numerical analyses of circular hole using the properties for TYPE-2 rock mass were carried out. The magnitude or size of plastic region and radial displacement in case of lower bound properties is about 4 times larger than that of upper bound properties.

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Expert System for the Design of the Preloading Method (선행재하 공법 설계를 위한 전문가 시스템)

  • 김병일;김명모
    • Geotechnical Engineering
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    • v.10 no.1
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    • pp.83-102
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    • 1994
  • Design practice of the preloading method, which is one of the most used ground improvement methods, includes quite complicated problems, especially when the draining facilities such as rand drain piles are to be considered. But, such complicated problems can be easily handled once an expert system is developed. The expert system is an interactive computer program which has just succeeded in commercial application. It is a new field of CAE(computer aided engineering), which has developed on application of geotechnical problems in recent years In this study, the expert system which gives practical assistance to engineers is developed by building the knowledge base for the preloading method with vertical drains. In this study, an expert system is built by using CLIPS as a development tool. And the expert system is developed under the workstation environment using UNIX OS.

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Automated Data Extraction from Unstructured Geotechnical Report based on AI and Text-mining Techniques (AI 및 텍스트 마이닝 기법을 활용한 지반조사보고서 데이터 추출 자동화)

  • Park, Jimin;Seo, Wanhyuk;Seo, Dong-Hee;Yun, Tae-Sup
    • Journal of the Korean Geotechnical Society
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    • v.40 no.4
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    • pp.69-79
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    • 2024
  • Field geotechnical data are obtained from various field and laboratory tests and are documented in geotechnical investigation reports. For efficient design and construction, digitizing these geotechnical parameters is essential. However, current practices involve manual data entry, which is time-consuming, labor-intensive, and prone to errors. Thus, this study proposes an automatic data extraction method from geotechnical investigation reports using image-based deep learning models and text-mining techniques. A deep-learning-based page classification model and a text-searching algorithm were employed to classify geotechnical investigation report pages with 100% accuracy. Computer vision algorithms were utilized to identify valid data regions within report pages, and text analysis was used to match and extract the corresponding geotechnical data. The proposed model was validated using a dataset of 205 geotechnical investigation reports, achieving an average data extraction accuracy of 93.0%. Finally, a user-interface-based program was developed to enhance the practical application of the extraction model. It allowed users to upload PDF files of geotechnical investigation reports, automatically analyze these reports, and extract and edit data. This approach is expected to improve the efficiency and accuracy of digitizing geotechnical investigation reports and building geotechnical databases.

An optimal classification method for risk assessment of water inrush in karst tunnels based on grey system theory

  • Zhou, Z.Q.;Li, S.C.;Li, L.P.;Shi, S.S.;Xu, Z.H.
    • Geomechanics and Engineering
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    • v.8 no.5
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    • pp.631-647
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    • 2015
  • Engineers may encounter unpredictable cavities, sinkholes and karst conduits while tunneling in karst area, and water inrush disaster frequently occurs and endanger the construction safety, resulting in huge casualties and economic loss. Therefore, an optimal classification method based on grey system theory (GST) is established and applied to accurately predict the occurrence probability of water inrush. Considering the weights of evaluation indices, an improved formula is applied to calculate the grey relational grade. Two evaluation indices systems are proposed for risk assessment of water inrush in design stage and construction stage, respectively, and the evaluation indices are quantitatively graded according to four risk grades. To verify the accuracy and feasibility of optimal classification method, comparisons of the evaluation results derived from the aforementioned method and attribute synthetic evaluation system are made. Furthermore, evaluation of engineering practice is carried through with the Xiakou Tunnel as a case study, and the evaluation result is generally in good agreement with the field-observed result. This risk assessment methodology provides a powerful tool with which engineers can systematically evaluate the risk of water inrush in karst tunnels.

Real-time Geotechnical Information Database Development Using Location Based Service (LBS를 이용한 실시간 지반정보 DB 구축 시스템 개발)

  • Woo, Je-Yoon;Koo, Jee-Hee;Lee, Sang-Hoon
    • Journal of Korea Spatial Information System Society
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    • v.5 no.2 s.10
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    • pp.91-103
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    • 2003
  • There are currently tremendous amount of geotechnical information saved, which has been qcquired for essential application of site selection, plan, design, constructin, repari in the builing work. However, due to the lack of the location data attribute, there has been a trouble in its analysis and GIS implementation. In this study, the geotechnical information aquisition program(PGeo) for real-time database in the field and geotechnical information reporting program(GeoReport) by Web-GIS for additional data input and its reporting function has been developed.

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Multi-sensor data fusion based assessment on shield tunnel safety

  • Huang, Hongwei;Xie, Xin;Zhang, Dongming;Liu, Zhongqiang;Lacasse, Suzanne
    • Smart Structures and Systems
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    • v.24 no.6
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    • pp.693-707
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    • 2019
  • This paper proposes an integrated safety assessment method that can take multiple sources data into consideration based on a data fusion approach. Data cleaning using the Kalman filter method (KF) was conducted first for monitoring data from each sensor. The inclination data from the four tilt sensors of the same monitoring section have been associated to synchronize in time. Secondly, the finite element method (FEM) model was established to physically correlate the external forces with various structural responses of the shield tunnel, including the measured inclination. Response surface method (RSM) was adopted to express the relationship between external forces and the structural responses. Then, the external forces were updated based on the in situ monitoring data from tilt sensors using the extended Kalman filter method (EKF). Finally, mechanics parameters of the tunnel lining were estimated based on the updated data to make an integrated safety assessment. An application example of the proposed method was presented for an urban tunnel during a nearby deep excavation with multiple source monitoring plans. The change of tunnel convergence, bolt stress and segment internal forces can also be calculated based on the real time deformation monitoring of the shield tunnel. The proposed method was verified by predicting the data using the other three sensors in the same section. The correlation among different monitoring data has been discussed before the conclusion was drawn.