• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.2
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• pp.249-260
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• 2014

When a train enters the tunnel at high speed, the pressure wave occurs. When this pressure wave reaches at the exit of tunnel, some are either emitted to the outside or reflected in tunnel by the form of expansion wave. The wave emitted to the outside forms the impulsive pressure wave. This wave is called 'Micro Pressure Wave'. The micro pressure wave generates noise and vibration around a exit portal of tunnel. When it becomes worse, it causes anxiety for residents and damage to windows. Thus, it requires a counterplan and prediction about the micro pressure wave for high speed railway construction. In this paper, the effects of train head nose and tunnel portal shape were investigated by model test, measurement for the micro pressure wave at the operating tunnel as well as numerical analysis for the gradient of pressure wave in the tunnel. As results, a method for predicting the intensity of the micro pressure wave is suggested and then the intensity of the micro pressure wave is analyzed by the tunnel length and the cross-sectional area.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.39-47
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• 2003

Rockbursts are mainly caused by a sudden release or the stored strain energy in the rock mass. They have been the major hazard in deep hard rock mines but rarely occur in tunnels. Due to the short history and limited information on rockbursts, the topic has rarely been studied in Korea. Some cases of rockbursts, however, have been reported during construction of a mountain tunnel for waterway. This study focuses on analyzing data on rockbursts obtained from a TBM (Tunnel Boring Machine) tunnel and suggests methods for a comprehensive understanding on rockbursts. From the analysis of the field data of rockbursts, it was found that most rockbursts mainly occurred at the section between the tunnel face and the TBM operating room, and the rock bursting phenomena lasted up to 20 days after excavation in certain areas. The data also show that the bursting spots are located all around the tunnel surface including the face, the wall, and the roof, The maximum size of bursting spots is usually less than 100cm. This study also suggests new scale systems of brittleness and uniaxial compressive strength to evaluate the possible tendency for a rockburst. These systems are scaled based on the scale system of strain energy density. In addition, with these scale systems, this research shows that there are potentially higher tendencies for rockbursts in this specific tunnel. Moreover this research suggests that properties of rock and rock mass, RMR (Rock Mass Rating) value, tunneling method, excavating speed, and depth of tunnel have a strong correlation with rockbursts.

• The KSFM Journal of Fluid Machinery
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• v.14 no.5
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• pp.63-68
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• 2011

This paper presents an optimization procedure for performance improvement of a tunnel ventilation jet fan. Optimization techniques based on response surface approximation (RSA) are employed to improve the aerodynamic performance of a tunnel ventilation jet fan. For numerical analysis, three-dimensional Renolds- averaged Navier-Stokes (RANS) equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the total efficiency at the operating condition as the objective function. Four geometric variables defining the meridional length and the thickness profile at the hub and shroud in the jet fan rotor are selected as design variables for the numerical optimization. The results of the numerical optimization show that the total efficiency of the optimized model is significantly improved in comparison with the base model.

• Wind and Structures
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• v.29 no.6
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• pp.405-416
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• 2019

Aerodynamic characteristic of a small scale wind turbine under the influence of an incoming uniform wind field is studied using k-ω Shear Stress Transport turbulence model. Firstly, the lift and drag characteristics of the blade section consisting of S826 airfoil is studied using 2D simulations at a Reynolds number of 1×10⁵. After that, the full turbine including the rotational effects of the blade is simulated using Multiple Reference Frames (MRF) and Sliding Mesh Interface (SMI) numerical techniques. The differences between the two techniques are quantified. It is then followed by a detailed comparison of the turbine's power/thrust output and the associated wake development at three tip speeds ratios (λ = 3, 6, 10). The phenomenon of blockage effect and spatial features of the flow are explained and linked to the turbines power output. Validation of wake profiles patterns at multiple locations downstream is also performed at each λ. The present work aims to evaluate the potential of the numerical methods in reproducing wind tunnel experimental results such that the method can be applied to full-scale turbines operating under realistic conditions in which observation data is scarce or lacking.

• Smart Structures and Systems
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• v.6 no.3
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• pp.239-262
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• 2010

Tube Lines has carried out a "knowledge and investigation programme" on the deep tube tunnels comprising the Jubilee, Northern and Piccadilly lines, as required by the PPP contract with London Underground. Many of the tunnels have been in use for over 100 years, so this assessment was considered essential to the future safe functioning of the system. This programme has involved a number of generic investigations which guide the assessment methodology and the analysis of some 5,000 individual structures. A significant amount of investigation has been carried out, including ultrasonic thickness measurement, detection of brickwork laminations using radar, stress measurement using magnetic techniques, determination of soil parameters using CPT, pressuremeter and laboratory testing, installation of piezometers, material and tunnel segment testing, and trialling of remote photographic techniques for inspection of large tunnels and shafts. Vibrating wire, potentiometer, electro level, optical and fibre-optic monitoring has been used, and laser measurement and laser scanning has been employed to measure tunnel circularity. It is considered that there is scope for considerable improvements in non-destructive testing technology for structural assessment in particular, and some ideas are offered as a "wish-list". Assessment reports have now been produced for all assets forming Tube Lines' deep tube tunnel network. For assets which are non-compliant with London Underground standards, the risk to the operating railway has to be maintained as low as reasonably practicable (ALARP) using enhanced inspection and monitoring, or repair where required. Monitoring techniques have developed greatly during recent years and further advances will continue to support the economic whole life asset management of infrastructure networks.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.2207-2212
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• 2008

The next generation of Korean high-speed train under development will be designed for the maximum operating speed of 350km/h and maximum speed of 400km/h. This high-speed operation may cause the noise and vibration problems around tunnel exit due to the higher micro-pressure wave than present level. In this study, the nose shape optimization was conducted for the countermeasure against these problems. Axi-symmetric solver was used for numerical simulation, and response surface was used for efficiency of optimization process. Also the multi-step optimization was conducted to find out more accurate optimal shape. Through these analysis and optimization, it was found out that the optimal nose shapes for minimization of micro-pressure wave are definitely different along the nose length variation. And the mechanism of micro-pressure wave reduction was closely investigated by the analysis of generation process of compression wave in tunnel. The results are expected to be used as design guideline for performance improvement of the next generatin of Korean high-speed train.

• Tunnel and Underground Space
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• v.12 no.2
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• pp.115-119
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• 2002

Four tunnels have been planned to operate a large diameter shielded TBM in Gwangju urban subway construction site. No.1 tunnel has completely been excavated for 13 months operating. Net penetration rate and its relations with thrust farce of the shielded TBM are analysis in this report. This shallow depth tunnel of 536m length is located in soil layers at launching and in hard rocks at ending with 84 m length. The weekly net penetration rates haute dropped down as low as 20∼110 mm/hr in rock while 400∼800 mm/hr in soil. The actual penetration rates we proved to be high as the theoretical penetration rate which is analysis in consideration of conditions of machine and rock. And net penetration rate is investigated to increase linearly thrust force.

• Geomechanics and Engineering
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• v.29 no.5
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• pp.523-533
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• 2022

Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R²≥0.79; whereas, a one-step prediction is R²≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R² and UPD is proposed. When UPD increases R² decreases exponentially; In particular, UPD at R²=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R² value targeted by an operator. Therefore, a calculation process for the equation between the R² and UPD is addressed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.185-189
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• 2001

In order to prevent the production defects the optimum design of product, jig and fixture putting in the field is very significant manufacturing method. Drilling Jig is the device according to industrial demand for multi manufacturing products on the growing at alarming rate. In the field of design and making for machine tool working, welding, assembling with jig and fixture for mass production is a specific division. They require analysis of many kinds of important factors, theory and practice of machine tool operating process and jig & fixture structure, machining condition for tool making, tool materials, heat treatment of jig & fixture components, know-how and so on. In this study we designed and constructed a drilling jig of mass production and performed tryout under the Auto CAD, Auto Lisp database, that we made by database, and window environment. Especially this study is reveals with the analysis of part drawing, jig planning, jig design etc, and then the result of drill jig's making try out.