• Geomechanics and Engineering
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• v.34 no.5
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• pp.491-505
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• 2023

The practical usage of underground space and demand for vehicular tunnels necessitate the construction of non-circular wide rectangular tunnels. However, constructing large tunnels in soft clayey soil conditions with no ground improvement can lead to excessive ground deformations and collapse. In recent years, in situ ground improvement techniques such as jet grouting and deep cement mixing are often utilized to perform cement-stabilisation around the tunnel boundary to prevent large deformations and failure. This paper discusses the stability characteristics and failure behaviour of a wide rectangular tunnel in cement-treated soft clays. First, the plane strain finite element model is developed and validated with the results of centrifuge model tests available in the past literature. The critical tunnel support pressures computed from the numerical study are found to be in good agreement with those of centrifuge model tests. The influence of varying strength and thickness of improved soil surround, and cover depth are studied on the stability and failure modes of a rectangular tunnel. It is observed that the failure behaviour of the tunnel in improved soil surround depends on the ratio of the strength of improved soil surround to the strength of surrounding soil, i.e., q_ui/q_us, rather than just q_ui. For low q_ui/q_us ratios,the stability increases with the cover; however, for the high strength improved soil surrounds with q_ui >> q_us, the stability decreases with the cover. The failure chart, modified stability equation, and stability chart are also proposed as preliminary design guidelines for constructing rectangular tunnels in the improved soil surrounded by soft clays.

• Wind and Structures
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• v.12 no.4
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• pp.299-312
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• 2009

It has long been studied about the flow around bluff bodies, but the effect of aspect ratio on the sharp-edged bodies in thick turbulent boundary layers is still argued. The author investigates the flow characteristics around a series of rectangular bodies ($40^d{\times}80^w{\times}80^h$, $80^d{\times}80^w{\times}80^h$ and $160^d{\times}80^w{\times}80^h$ in mm) placed in a deep turbulent boundary layer. The study is aiming to identify the extant Reynolds number independence of the rectangular bodies and furthermore understand the surface pressure distribution around the bodies such as the suction pressure in the leading edge, when the shape of bodies is changed, responsible for producing extreme suction pressures around the bluff bodies. The experiments are carried out at three different Reynolds numbers, based on the velocity U at the body height h, of 24,000, 46,000 and 67,000, and large enough that the mean boundary layer flow is effectively Reynolds number independent. The experiment includes wind tunnel work with the velocity and surface pressure measurements. The results show that the generation of the deep turbulent boundary layer in the wind tunnel and the surface pressure around the bodies were all independent of Reynolds number and the longitudinal length, but highly dependent of the transverse width.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.10a
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• pp.46-55
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• 2006

There are many kinds of braced cut wall methods as the sheet pile, SCW, CIP and slurry wall which is adoptable for a deep excavation construction in a coastal filled land. The braced cut wall which has a strong stiffness is very stable but it has the weak point that the construction cost is high. Thus when a braced cut wall is designed, the geotechnical engineers choose the braced cut wall which has more safe and economic in the consideration of surrounding buildings near the construction site. Especially, when the sheet pile method as a braced cut wall is cheesed, the layer order and consistence of a coastal deposit stratum are considered and the pile driving method is also considered. This paper introduces the case that the originally box-type sheet pile wall was changed to U-type and high strength material after the pilot test at the subway construction site in a coastal filled land. This paper also introduces the case that the sheet pile's driving method was changed to special method in the section of the temporary coffer dam which had made when the present coastal filled land was formed.

• Geomechanics and Engineering
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• v.15 no.4
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• pp.973-986
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• 2018

The objective of this paper is to present abacuses obtained from a parametric study of deep-lined tunnels using a numerical finite element model. This numerical model was implemented in software GEOMEC91, which is a two-dimensional axisymmetric model that considers the progress of excavation and the placing of the lining through the activation and deactivation of elements. It is adopted a step of excavation constant (1/3 of radius), constant velocity and circular cross section along the tunnel axis. It is used for rock mass a viscoplastic constitutive law with von-Mises criterion of viscoplasticity without hardening whose deformation rate over time is given by the Bingham model. The lining uses a linear elastic constitutive law. In total are 1716 analysis presented in 60 abacuses that show the value of ultimate convergence ($U_{eq}$) due to tunneling speed. In addition, it is shown an example of the use of the abacuses to determine the ultimate convergence ($U_{eq}$) of the tunnel and pressure ($P_{eq}$) on the lining.

• Structural Engineering and Mechanics
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• v.77 no.4
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• pp.495-508
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• 2021

This study devises a novel approach, namely quadruple 1D convolutional neural network, for detecting connection stiffness reduction in steel truss bridge structure using experimental and numerical modal data. The method is developed based on expertise in two domains: firstly, in Structural Health Monitoring, the mode shapes and its high-order derivatives, including second, third, and fourth derivatives, are accurate indicators in assessing damages. Secondly, in the Machine Learning literature, the deep convolutional neural networks are able to extract relevant features from input data, then perform classification tasks with high accuracy and reduced time complexity. The efficacy and effectiveness of the present method are supported through an extensive case study with the railway Nam O bridge. It delivers highly accurate results in assessing damage localization and damage severity for single as well as multiple damage scenarios. In addition, the robustness of this method is tested with the presence of white noise reflecting unavoidable uncertainties in signal processing and modeling in reality. The proposed approach is able to provide stable results with data corrupted by noise up to 10%.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.435-444
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• 2023

In the licensing application for the deep geological disposal system of high-level radioactive waste in Finland, the disposal tunnel backfilling has been changed from the block/pellet (for the construction) to the granular type (for the operation). Accordingly, for establishing the design concept for backfilling, it is necessary to examine applicability to the domestic facility through analyzing problems of the existing method and improvements in the alternative design. In this paper, we first reviewed the principal studies conducted for changing the backfill method in the licensing process of the Finnish facility, and identified the expected problems in applying the block/pellet backfill method. In addition, we derived the evaluation factors to be considered in terms of technical and operational aspects for the backfilling solution, and then conducted a comparative analysis for two types of backfill methods. This analysis confirmed the overall superiority of the design change. It is expected that these results could be utilized as the technical basis for deriving the optimum design plan in development process of the Korean-specific deep disposal facility. However, applicability should be reviewed in advance based on the latest technical data for the detailed evaluation factors that must be considered for selecting the backfilling method.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.302-314
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• 2024

Purpose: This study proposes a fall detection model based on a top-down deep learning pose estimation model to automatically determine falls of multiple workers in an underground utility tunnel, and evaluates the performance of the proposed model. Method: A model is presented that combines fall discrimination rules with the results inferred from YOLOv8-pose, one of the top-down pose estimation models, and metrics of the model are evaluated for images of standing and falling two or fewer workers in the tunnel. The same process is also conducted for a bottom-up type of pose estimation model (OpenPose). In addition, due to dependency of the falling interference of the models on worker detection by YOLOv8-pose and OpenPose, metrics of the models for fall was not only investigated, but also for person. Result: For worker detection, both YOLOv8-pose and OpenPose models have F1-score of 0.88 and 0.71, respectively. However, for fall detection, the metrics were deteriorated to 0.71 and 0.23. The results of the OpenPose based model were due to partially detected worker body, and detected workers but fail to part them correctly. Conclusion: Use of top-down type of pose estimation models would be more effective way to detect fall of workers in the underground utility tunnel, with respect to joint recognition and partition between workers.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.133-133
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• 2009

It is desirable to choose a high-k material having a large band offset with the tunneling oxide and a deep trapping level for use as the charge trapping layer to achieve high PIE (Programming/erasing) speeds and good reliability, respectively. In this paper, charge trapping and tunneling characteristics of high-k hafnium oxide ($HfO_2$) layer with various thicknesses were investigated for applications of tunnel barrier engineered nonvolatile memory. A critical thickness of $HfO_2$ layer for suppressing the charge trapping and enhancing the tunneling sensitivity of tunnel barrier were developed. Also, the charge trap centroid and charge trap density were extracted by constant current stress (CCS) method. As a result, the optimization of $HfO_2$ thickness considerably improved the performances of non-volatile memory(NVM).

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.5
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• pp.563-573
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• 2015

For hard rock subsea tunnels the most challenging rock mass conditions are in most cases represented by major faults/weakness zones. Poor stability weakness zones with large water inflow can be particularly problematic. At the pre-construction investigation stage, geological and engineering geological mapping, refraction seismic investigation and core drilling are the most important methods for identifying potentially adverse rock mass conditions. During excavation, continuous engineering geological mapping and probe drilling ahead of the face are carried out, and for the most recent Norwegian subsea tunnel projects, MWD (Measurement While Drilling) has also been used. During excavation, grouting ahead of the tunnel face is carried out whenever required according to the results from probe drilling. Sealing of water inflow by pre-grouting is particularly important before tunnelling into a section of poor rock mass quality. When excavating through weakness zones, a special methodology is normally applied, including spiling bolts, short blast round lengths and installation of reinforced sprayed concrete arches close to the face. The basic aspects of investigation, support and tunnelling for major weakness zones are discussed in this paper and illustrated by cases representing two very challenging projects which were recently completed (Atlantic Ocean tunnel and T-connection), one which is under construction (Ryfast) and one which is planned to be built in the near future (Rogfast).

• ETRI Journal
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• v.43 no.1
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• pp.40-52
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• 2021

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.