• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.284-289
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• 2019

The Korea Foldable safe pathway system is an evacuation support system to get temporary evacuation route in railway tunnel and large space fires. A prevention smoke screen is unfolded in fires and it is needed to prevent heat and smoke from fire source. Therefore, ventilation system for positive pressure condition is equipped with foldable safe pathway system. Numerical analyses of temperature and pressure distribution with distance from fire source were performed considering fire scenario of new train vehicle. The smoke temperatures did not exceed $200^{\circ}C$ that distance from the fire source was more than 20 m and smoke pressure was reduced with distance from fire source. Maximum smoke pressure was 14 Pa and average pressure was 6 Pa in position of prevention smoke screen. As results, to install foldable safe pathway system, ventilation system is need to maintain 6 Pa positive pressure condition.

• Wind and Structures
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• v.32 no.2
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• pp.127-142
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• 2021

Wind load acting on a standalone structure is different from that acting on a similar structure which is surrounded by other structures in close proximity. The presence of other structures in the surrounding can change the wind flow regime around the principal structure and thus causing variation in wind loads compared to a standalone case. This variation on wind loads termed as interference effect depends on several factors like terrain category, geometry of the structure, orientation, wind incident angle, interfering distances etc., In the present study, a three building configuration is considered and the mean pressure coefficients on each face of principle building are determined in presence of two interfering buildings. Generally, wind loads on interfering buildings are determined from wind tunnel experiments. Computational fluid dynamic studies are being increasingly used to determine the wind loads recently. Whereas, wind tunnel tests are very expensive, the CFD simulation requires high computational cost and time. In this scenario, Artificial Neural Network (ANN) technique and Support Vector Regression (SVR) can be explored as alternative tools to study wind loads on structures. The present study uses these data-driven approaches to predict mean pressure coefficients on each face of principle building. Three typical arrangements of three building configuration viz. L shape, V shape and mirror of L shape arrangement are considered with varying interfering distances and wind incidence angles. Mean pressure coefficients (Cp mean) are predicted for 45 degrees wind incidence angle through ANN and SVR. Further, the critical faces of principal building, critical interfering distances and building arrangement which are more prone to wind loads are identified through this study. Among three types of building arrangements considered, a maximum of 3.9 times reduction in Cp mean values are noticed under Case B (V shape) building arrangement with 2.5B interfering distance. Effect of interfering distance and building arrangement on suction pressure on building faces has also been studied. Accordingly, Case C (mirror of L shape) building arrangement at a wind angle of 45º shows less suction pressure. Through this study, it was also observed that the increase of interfering distance may increase the suction pressure for all the cases of building configurations considered.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.291-300
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• 2022

Tunnel boring machines combined with the earth pressure balanced shield method (EPB shield TBMs) have been adopted in urban areas as they allow excavation of tunnels with limited ground deformation through continuous and repetitive excavation and support. Nevertheless, the expansion of TBM construction requires much more minor and exquisitely controlled surface settlement to prevent economic loss. Several parametric studies controlling the tunnel's geometry, ground properties, and TBM operational factors assuming ordinary conditions for EPB shield TBM excavation have been conducted, but the impact of excessive excavation on the induced settlement has not been adequately studied. This study conducted a numerical evaluation of surface settlement induced by the ground loss from face imbalance, excessive excavation, and tail void grouting. The numerical model was constructed using FLAC3D and validated by comparing its result with the field data from literature. Then, parametric studies were conducted by controlling the ground stiffness, face pressure, tail void grouting pressure, and additional volume of muck discharge. As a result, the contribution of these operational factors to the surface settlement appeared differently depending on the ground stiffness. Except for the ground stiffness as the dominant factor, the order of variation of surface settlement was investigated, and the volume of additional muck discharge was found to be the largest, followed by the face pressure and tail void grouting pressure. The results from this study are expected to contribute to the development of settlement prediction models and understanding the surface settlement behavior induced by TBM excavation.

• Clinics in Shoulder and Elbow
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• v.26 no.2
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• pp.140-147
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• 2023

Background: The management of acromioclavicular (AC) joint dislocation remains controversial. Recently, anatomic coracoclavicular (CC) fixation with a double clavicular tunnel and three flip-buttons has shown promising results. This study aimed to evaluate functional and radiological outcomes in patients with high-grade AC joint dislocation treated with anatomic CC fixation using double clavicular tunnels and three flip-buttons. Methods: A retrospective, unicentric study was performed. The study included patients with high-grade AC joint dislocation who underwent surgery with anatomic CC fixation using double clavicular tunnels and three flip-buttons. Demographic data were obtained from medical records. A functional evaluation using subjective shoulder value (SSV), visual analog scale (VAS), and disabilities of the arm, shoulder, and hand (DASH) questionnaires was performed, and an evaluation of preoperative and postoperative comparative Zanca view images was performed. Factors associated with functional outcomes and radiological AC reduction were analyzed. Results: A total of 83 patients completed follow-up and were included in the analysis. The mean SSV, VAS, and DASH scores were 92.8, 0.8, and 6.4, respectively. Patients who had complications experienced significantly worse functional outcomes (DASH: P=0.037). Suboptimal final AC reduction was observed in nine patients (11.1%), and significantly more frequently in patients older than 40 years (P=0.031) and in surgeries performed more than 7 days after injury (P=0.034). There were two reoperations (2.4%). Conclusions: Anatomic CC fixation with a double clavicular tunnel and three flip-buttons leads to good functional outcomes, low complication rates, and high rates of optimal AC reduction.

• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.2
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• pp.157-164
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• 2010

Recently, the number of shallow tunnel construction increases to improve the structural safety and environment-friendliness. In semi-cut-and-cover Method, ground is excavated to the crown arch level and arch slab is set to backfill before the excavation of lower face. In this study, laboratory model tests was performed to clarify the behavior of the arch slab constructed perpendicular to the slope. Results show that Arch slab is affected by perpendicular to the slope and bedrocks. Negative moment at the upper part of the arch slab at hillside and positive moment at the upper part at the other side are generated as perpendicular to the slope increases. Reaction load at the hillside support was larger than that at the other side.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.163-174
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• 2024

Currently, the urban railway operating agency is improving the emergency telephone in operation into an IP-based "trackside integrated interface communication facility" that can support a variety of additional services in order to quickly respond to emergency situations within the tunnel. This study is based on this Analyze the needs of various stakeholders regarding the design of a system architecture that establishes an IoT sensor network environment to detect abnormal situations in the tunnel and transmits the collected information to the control center to predict disaster situations in advance, and defines the system requirements. In addition, a scenario model for disaster response was provided through the presentation of a service model. Through this, the perspective of responding to urban railway disasters changes from reactive response to proactive prevention, thereby ensuring safe operation of urban railways and preventing major industrial accidents.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• Tunnel and Underground Space
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• v.17 no.5
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• pp.411-427
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• 2007

Reliability in tunnel analysis is necessary to accomplish technically sound design and economical construction. For this, a thorough understanding of the construction procedure including the ground-support interaction has to be obtained. This paper describes a proper modelling technique to simulate the behavior of the steel fiber reinforced shotcrete (SFRS) which maintain the supporting capability in post-failure regime. The additional supporting effect of the steel support was also verified by 3-D analyses and a new load distribution factor were proposed. The use of the plastic moment limit (PML) alone can eliminate the occurrence of the awkwardly high tensile stress in the shotcrete and can successfully model the post-peak ductile behavior of the SFRS. But with this method, moment is limited whenever the stress caused by moment reaches tensile strength of the shotcrete irrespective of the stress by axial force. Therefore, it was necessary to find a more comprehensive method which can reflect the influence of the moment and axial force. This can be accomplished by the proper use of "liner element" which is the built-in model in FLAC. In this model, the peak and residual strength as well as the uniaxial compressive strength of the SFRS can be specified. Analyses were conducted with these two models on the 2-lane road tunnels excavated in class IV and V rock mass and results were compared with the conventional elastic beam model. Results showed that both models can reflect the fracture toughness of the SFRS which could not be accomplished by the elastic beam model.

• The Journal of Engineering Geology
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• v.20 no.1
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• pp.101-109
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• 2010

There are many slopes generally developed by excavation and cut slope with small steps on massive slopes of roads. Especially these cut slopes which excavating around fault fracture zone need a reinforcement technology in order to ensure safety. In the case of slope excavation, it is difficult to use the existing slope support at fracture zone because of geological characteristics. Especially the factor of safety decreases significantly due to the movement of blocks in bed rocks and the expansion of interspace of discontinuous planes in fractured zones caused by excavation. Thus an efficient reinforcement technique in accordance with geological properties of fracture zones needs to be developed because the existing slope support has a restricted application. Therefore it is necessary to develop the specialized rock bolt technique in order to ensure an efficient factor of safety for anomalous fracture zones in slopes and tunnels. The purpose of this study is to develop newly improved rock bolt to increase a supporting effect of the swellex bolt method used recently as a friction type in fracture zones.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.540-550
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• 2020

Machine learning has been actively used in the field of automation due to the development and establishment of AI technology. The important thing in utilizing machine learning is that appropriate algorithms exist depending on data characteristics, and it is needed to analysis the datasets for applying machine learning techniques. In this study, advance rate is predicted using geotechnical and machine data of TBM tunnel section passing through the soil ground below the stream. Although there were no problems of application of statistical technology in the linear regression model, the coefficient of determination was 0.76. While, the ensemble model and support vector machine showed the predicted performance of 0.88 or higher. it is indicating that the model suitable for predicting advance rate of the EPB Shield TBM was the support vector machine in the analyzed dataset. As a result, it is judged that the suitability of the prediction model using data including mechanical data and ground information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of data.