• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• Journal of Korean Tunnelling and Underground Space Association
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• v.4 no.4
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• pp.277-286
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• 2002

Most of the problems in dealing with the tunnel construction are the uncertainties and complexities of the stress conditions and rock strengths in ahead of the tunnel excavation. The limitations on the investigation technology, inaccessibility of borehole test in mountain area and public hatred also restrict our knowledge on the geologic conditions on the mountainous tunneling area. Nevertheless an extensive and superior geophysical exploration data is possibly acquired deep within the mountain area, with up to the tunnel locations in the case of alternative design or turn-key base projects. An appealing claim in the use of artificial neural networks (ANN) is that they give a more trustworthy results on our data based on identifying relevant input variables such as a little geotechnical information and biological learning principles. In this study, error back-propagation algorithm that is one of the teaching techniques of ANN is applied to presupposition on Rock Mass Ratings (RMR) for unknown tunnel area. In order to verify the applicability of this model, a 4km railway tunnel's field data are verified and used as input parameters for the prediction of RMR, with the learned pattern by error back propagation logics. ANN is one of basic methods in solving the geotechnical uncertainties and helpful in solving the problems with data consistency, but needs some modification on the technical problems and we hope our study to be developed in the future design work.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.5
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• pp.187-194
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• 2010

As the design of the pillar width (PW) of the parallel tunnels in downtown area, in which are located in plains zone with deep alluvium compared with mountain tunnels, is directly related with pre-compensation payment and costs of the underground area, it has to be planned as to keep minimum distance while securing the stability of the parallel tunnels. Although PW of downtown road tunnel in Korea is standardized as 1.5D(D: diameter of the tunnels), PW sometimes has to be reduced within 1.5D to adjust the tunnel lines to the city plan in the cases of the inlet and outlet of the tunnels. In this paper, the design and the analyses of optimum PW of the NATM type road tunnel in the downtown area are introduced. The relationship among the tunnel line planning and underground compensation fee, and ground characteristics are evaluated. In the determination of PW distance, the numerical analyses of underground road tunnels were performed, including the use of the strength decrease method and strength/stress ratio method. In the cases of inlet and outlet part of the tunnels where the stability of the pillars is poor due to contiguous construction of the parallel tunnels, the reinforcement methods are recommended for securing the stability. Numerical verification was performed for the reinforcement proposed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.3
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• pp.239-248
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• 2020

Exact rock classification helps suitable support patterns to be installed. Face mapping is usually conducted to classify the rock mass using RMR (Rock Mass Ration) or Q values. There have been several attempts to predict the grade of rock mass using mechanical data of jumbo drills or probe drills and photographs of excavation surfaces by using deep learning. However, they took long time, or had a limitation that it is impossible to grasp the rock grade in ahead of the tunnel surface. In this study, a method to predict the Q value ahead of excavation surface is developed using recurrent neural network (RNN) technique and it is compared with the Q values from face mapping for verification. Among Q values from over 4,600 tunnel faces, 70% of data was used for learning, and the rests were used for verification. Repeated learnings were performed in different number of learning and number of previous excavation surfaces utilized for learning. The coincidence between the predicted and actual Q values was compared with the root mean square error (RMSE). RMSE value from 600 times repeated learning with 2 prior excavation faces gives a lowest values. The results from this study can vary with the input data sets, the results can help to understand how the past ground conditions affect the future ground conditions and to predict the Q value ahead of the tunnel excavation face.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.209-227
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• 2023

The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.727-736
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• 2021

Road tunnel lengths are increasing. Some 1,300 tunnels with 1,102 km in length had been increased till 2019 from 2010. There are 64 tunnels over 3,000 m in length, with their total length adding up to 276.7 km. Safety facilities in the event of a tunnel fire are critical so as to prevent large-scale casualties. Standards for installing disaster prevention facilities are being proposed based on the guidelines of the Ministry of Land, Infrastructure and Transport, but they may be limited to deep underground tunnels. This study was undertaken to provide guidelines for the spacing of evacuation connection passages and the widths of evacuation connection doors. Evacuation with various spacing and widths was simulated in regards to evacuation time, which is the measure of safety, using the evacuation analysis simulation software EXODUS Ver.6.3 and the fire/smoke analysis software SMARTFIRE Ver.4.1. Evacuation connection gates with widths of 0.9 m and 1.2 m, and spacings of 150 m to 250 m, were set to every 20 m. In addition, longitudinal slopes of 6 % and 0 % were considered. It was determined to be safe when the evacuation completion time was shorter than the delay diffusion time. According to the simulation results, all occupants could complete evacuation before smoke spread regardless of the width of the evacuation connection door when the longitudinal slope was 6 % and the interval of evacuation connection passage was 150 m. When the evacuation connection passage spacing was 200 m and the evacuation connection gate width was 1.2 m, all occupants could evacuate when the longitudinal slope was 0 %. Due to difference in evacuation speed according to the longitudinal slope, the evacuation time with a 6 % slope was 114 seconds shorter (with the 190 m connection passage) than with a 0 % slope. A shorter spacing of evacuation connection passages may reduce the evacuation time, but this is difficult to implement in practice because of economic and structural limitations. If the width of the evacuation junction is 1.2 m, occupants could evacuate faster than with a 0.9 m width. When the width of a connection door is 1.2 m with appropriate connection passage spacing, it might provide a means to increase economic efficiency and resolve structural limitations while securing evacuation safety.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.243-269
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• 2021

Since the early 2010s, the social importance of research and practical projects targeting deep geological disposal of high-level nuclear waste, underground CO₂ storage and characterization of deep subsurface by borehole investigation has been increasing. In this regard, there is also a significant increase in the need for in situ test technology to obtain quantitative and reliable information on the hydraulic characteristics of deep rock mass. Through years of research and development, we have independently set up Deep borehole Hydraulic Test System (DHTS) based on the key apparatuses designed and made with our own technology. Using this system, high precision constant pressure injection tests were successfully completed at the two 1 km boreholes located in Mesozoic granite and sedimentary rock regions, Gyeongju. During the field tests, it was possible to measure very low flow rate below 0.01 l/min with micro flow rate injection/control module. In this paper, the major characteristics of DHTS are introduced and also some results obtained from the high precision field tests under the deep and low permeable rock mass environment are briefly discussed.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.310-310
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• 2016

최근 NAND flash memory는 높은 집적성과 데이터의 비휘발성, 낮은 소비전력, 간단한 입, 출력 등의 장점들로 인해 핸드폰, MP3, USB 등의 휴대용 저장 장치 및 노트북 시장에서 많이 이용되어 왔다. 특히, 최근에는 smart watch, wearable device등과 같은 차세대 디스플레이 소자에 대한 관심이 증가함에 따라 유연하고 투명한 메모리 소자에 대한 연구가 다양하게 진행되고 있다. 대표적인 플래시 메모리 소자의 구조로 charge trapping type flash memory (CTF)가 있다. CTF 메모리 소자는 trap layer의 trap site를 이용하여 메모리 동작을 하는 소자이다. 하지만 작은 window의 크기, trap site의 열화로 인해 메모리 특성이 나빠지는 문제점 등이 있다. 따라서 최근, trap layer에 다양한 물질을 적용하여 CTF 소자의 문제점을 해결하고자 하는 연구들이 진행되고 있다. 특히, 산화물 반도체인 zinc oxide (ZnO)를 trap layer로 하는 CTF 메모리 소자가 최근 몇몇 보고 되었다. 산화물 반도체인 ZnO는 n-type 반도체이며, shallow와 deep trap site를 동시에 가지고 있는 독특한 물질이다. 이 특성으로 인해 메모리 소자의 programming 시에는 deep trap site에 charging이 일어나고, erasing 시에는 shallow trap site에 캐리어들이 쉽게 공급되면서 deep trap site에 갇혀있던 charge가 쉽게 de-trapped 된다는 장점을 가지고 있다. 따라서, 본 실험에서는 산화물 반도체인 ZnO를 trap layer로 하는 CTF 소자의 메모리 특성을 확인하기 위해 간단한 구조인 metal-oxide capacitor (MOSCAP)구조로 제작하여 메모리 특성을 평가하였다. 먼저, RCA cleaning 처리된 n-Si bulk 기판 위에 tunnel layer인 SiO2 5 nm를 rf sputter로 증착한 후 furnace 장비를 이용하여 forming gas annealing을 $450^{\circ}C$에서 실시하였다. 그 후 ZnO를 20 nm, SiO2를 30 nm rf sputter로 증착한 후, 상부전극을 E-beam evaporator 장비를 사용하여 Al 150 nm를 증착하였다. 제작된 소자의 신뢰성 및 내구성 평가를 위해 상온에서 retention과 endurance 측정을 진행하였다. 상온에서의 endurance 측정결과 1000 cycles에서 약 19.08%의 charge loss를 보였으며, Retention 측정결과, 10년 후 약 33.57%의 charge loss를 보여 좋은 메모리 특성을 가지는 것을 확인하였다. 본 실험 결과를 바탕으로, 차세대 메모리 시장에서 trap layer 물질로 산화물 반도체를 사용하는 CTF의 연구 및 계발, 활용가치가 높을 것으로 기대된다.

• Geomechanics and Engineering
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• v.16 no.4
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• pp.399-413
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• 2018

This paper addresses the issue of field measurement of excavation damage zone (EDZ) and its numerical simulation method considering both excavation unloading and blasting load effects. Firstly, a 2000 m-deep rock cavern in China is focused. A detailed analysis is conducted on the field measurement data regarding the mechanical response of rock masses subjected to excavation and blasting operation. The extent of EDZ is revealed 3.6 m-4.0 m, accounting for 28.6% of the cavern span, so it is significantly larger than rock caverns at conventional overburden depth. The rock mass mechanical response subjected to excavation and blasting is time-independent. Afterwards, based on findings of the field measurement data, a numerical evaluation method for EDZ determination considering both excavation unloading and blasting load effects is presented. The basic idea and general procedures are illustrated. It features a calibration operation of damage constant, which is defined in an elasto-plastic damage constitutive model, and a regression process of blasting load using field blasting vibration monitoring data. The numerical simulation results are basically consistent with the field measurement results. Further, some issues regarding the blasting loads, applicability of proposed numerical method, and some other factors are discussed. In conclusion, the field measurement data collected from the 2000 m-deep rock cavern and the corresponding findings will broaden the understanding of tunnel behavior subjected to excavation and blasting at great depth. Meanwhile, the presented numerical simulation method for EDZ determination considering both excavation unloading and blasting load effects can be used to evaluate rock caverns with similar characteristics.

• Tunnel and Underground Space
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• v.16 no.1 s.60
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• pp.11-25
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• 2006

The world's largest nucleon decay experiment facility is constructed at a depth of approximately 1,000 meters, in the Kamio Mine, Japan. The excavated cavern is consisted of a cylinder of 42.4 m high and a semi elliptical dome of 15.2 m high, with a bottom diameter of 40 m. The total excavation volume is approximately $69,000\;m^3$. Because of the character as a large cavern excavation in deep underground, there is many unknown factors in rock mechanics. Based on the results of rock test and numerical analysis, the monitoring of rock mass behavior accompanying progress of construction was performed by various instruments installed in the rock mass surrounding the cavern. The monitoring data was used in the study of measures for cavern stability.