• Title/Summary/Keyword: Underground Road

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A study on the utilization of abrasive waterjet for mechanical excavation of hard rock in vertical shaft construction (고강도 암반에서 수직구 기계굴착을 위한 연마재 워터젯 활용에 관한 연구)

  • Seon-Ah Jo;Ju-Hwan Jung;Hee-Hwan Ryu;Jun-Sik Park;Tae-Min Oh
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.5
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    • pp.357-371
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    • 2023
  • In cable tunnel construction using TBM, the vertical shaft is an essential structure for entrance and exit of TBM equipment and power lines. Since a shaft penetrates the ground vertically, it often encounters rock mass. Blasting or rock splitting methods, which are mainly used to the rock excavation, cause public complaints due to the noise, vibration and road occupation. Therefore, mechanical excavation using vertical shaft excavation machine are considered as an alternative to the conventional methods. However, at the current level of technology, the vertical excavation machine has limitation in its performance when applied for high strength rock with a compressive strength of more than 120 MPa. In this study, the potential utilization of waterjet technology as an excavation assistance method was investigated to improve mechanical excavation performance in the hard rock formations. Rock cutting experiments were conducted to verify the cutting performance of the abrasive waterjet. Based on the experimental result, it was found that ensuring excavation performance with respect to changing in ground conditions can be achieved by adjusting waterjet parameters such as standoff distance, traverse speed and water pressure. In addition, based on the relationship between excavation performance, uniaxial compressive strength and RQD, it was suggested that excavation performance could be improved by artificially creating joints using the abrasive waterjet. It is expected that these research results can be utilized as fundamental data for the introduction of vertical shaft excavation machines in the future.

Comparison of Machine Learning Models to Predict the Occurrence of Ground Subsidence According to the Characteristics of Sewer (하수관로 특성에 따른 지반함몰 발생 예측을 위한 기계학습 모델 비교)

  • Lee, Sungyeol;Kim, Jinyoung;Kang, Jaemo;Baek, Wonjin
    • Journal of the Korean GEO-environmental Society
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    • v.23 no.4
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    • pp.5-10
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    • 2022
  • Recently, ground subsidence has been continuously occurring in downtown areas, threatening the safety of citizens. Various underground facilities such as water and sewage pipelines and communication pipelines are buried under the road. It is reported that the cause of ground subsidence is the deterioration of various facilities and the reckless development of the underground. In particular, it is known that the biggest cause of ground subsidence is the aging of sewage pipelines. As an existing study related to this, several representative factors of sewage pipelines were selected and a study to predict the risk of ground subsidence through statistical analysis has been conducted. In this study, a data SET was constructed using the characteristics of OO city's sewage pipe characteristics and ground subsidence data, The data set constructed from the characteristics of the sewage pipe of OO city and the location of the ground subsidence was used. The goal of this study was to present a classification model for the occurrence of ground subsidence according to the characteristics of sewage pipes through machine learning. In addition, the importance of each sewage pipe characteristic affecting the ground subsidence was calculated.

Detection of Steel Ribs in Tunnel GPR Images Based on YOLO Algorithm (YOLO 알고리즘을 활용한 터널 GPR 이미지 내 강지보재 탐지)

  • Bae, Byongkyu;Ahn, Jaehun;Jung, Hyunjun;Yoo, Chang Kyoon
    • Journal of the Korean Geotechnical Society
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    • v.39 no.7
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    • pp.31-37
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    • 2023
  • Since tunnels are built underground, it is impossible to check visually the location and degree of deterioration of steel ribs. Therefore, in tunnel maintenance, GPR images are generally used to detect steel ribs. While research on GPR image analysis employing artificial neural networks has primarily focused on detecting underground pipes and road damage, there have been limited applications for analyzing tunnel GPR data, specifically for steel rib detection, both internationally and domestically. In this study, a one-step object detection algorithm called YOLO, based on a convolutional neural network, was utilized to automate the localization of steel ribs using GPR data. The performance of the algorithm is then analyzed. Two datasets were employed for the analysis. A dataset comprising 512 original images and another dataset consisting of 2,048 augmented images. The omission rate, which represents the ratio of undetected steel ribs to the total number of steel ribs, was 0.38% for the model using the augmented data, whereas the omission rate for the model using only the original data was 7.18%. Thus, from an automation standpoint, it is more practical to employ an augmented dataset.

A study on an interval of tunnel cross passage considering inclination and internal airflow (터널 내부 기류 변화에 따른 피난연락갱 간격 설정에 관한 연구)

  • Rie, Dong-Ho;Kim, Ha-Young;Yoo, Ji-Oh
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.12 no.1
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    • pp.43-49
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    • 2010
  • The escape connecting gallery in a tunnel on a road is one of emergency equipment to ensure safety for passer in the tunnel against the tunnel fire. Government stipulate over 500m tunnel has the cross passage at intervals of less then 250 m. However, this lump estimated interval is generated the concerns of exaggeration and under construction because peculiarity of the tunnel ex. The velocity of the tunnel airflow, an incline, degree of a fire, and innering area are not considered. The study indicate the way to estimate of the cross passage considered an incline and the velocity of the tunnel airflow for efficient application of cross passage on the tunnel design. As a result, in 0.0 m/s and 1.0 m/s of the velocity of the tunnel airflow case, the movement of smoke is influenced by the incline however, in 20 m/s case, it isn't influenced by incline much. According to the velocity of tunnel airflow and the incline, optimum interval of cross passage is not corresponded. Therefore established lump estimate that has 250 m intervals would be changed to estimate of optimum interval of cross passage that considered about the properties of tunnel, the velocity of the tunnel airflow, incline, degree of a fire and innering area of the tunnel.

A Study on the Change of Cavity Area through Groundwater Injection Test under Pavement Cavity (도로하부 공동 내의 지하수 주입 실험을 통한 공동 영역 변화 연구)

  • Kim, Sang Mok;Choi, Hyeon;Yoon, Jin Sung;Park, Jeong Jun
    • Journal of the Society of Disaster Information
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    • v.16 no.2
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    • pp.267-275
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    • 2020
  • Purpose: In this study, GPR exploration equipment, spray vehicles and flow meters, core drill, borehole image processing system(BIPS), 3D cavity imagery equipment, and cavity formatting equipment were used to identify this cavity growth process. Method: A certain amount of water was injected in proportion to the mass of the cavity, and the cavity was observed to expand as the injected water was drained out. The cavity rating change was evaluated by quantitatively evaluating the expansion factors and the speed of growth. Results: According to the results of examining the volume change through injection time - injection flow rate - volume increase for the four experimenters, the volume increase decreased as the injection time increased, and there was no further increase in volume if injected for one hour or so. Conclusion: In addition, the injection test analyzed the volumetric variation to determine whether the cause of the cavity occurrence was the effect of the underground burial in the vicinity of the cavity. Therefore, it was found that the cavity expansion is caused by the repetition of the relaxation soil collapse due to the groundwater flow and the loss of the collapsed soil below the cavity.

High Efficient Inductive Power Supply System Implemented for On Line Electric Vehicles

  • Huh, Jin;Park, Eun-Ha;Jung, Gu-Ho;Rim, Chun-Taek
    • Proceedings of the KIPE Conference
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    • 2009.11a
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    • pp.105-110
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    • 2009
  • The On Line Electric Vehicles(OLEV) that can pick up inductive power from underground coils on driving with high efficiency have been developed this year, and is now proposed in this paper. The IPS(Inductive Power Supply) system consists of power supply inverters, power supply rails, pick up modules, and a regulator. There are 3 generations of IPS have been developed so far, and the $4^{th}$ generation IPS is being developed. The $1^{st}$ generation has been demonstrated this Feb. 27, which is equipped with mechanically auto tracking pick-up module with 1cm air gap, and showed 80% power efficiency. The $2^{nd}$ generation IPS applied to an 120kW (average)/240kW(peak) motor powered electric bus has 17cm air gap with 72% power efficiency. For the $2^{nd}$ generation IPS, the Power supply inverter has 440V, 3phase input and 200A @ 20kHz output. The test power supply rail of 240m long is segmented by 60m each, where newly developed core structure and power cable are constructed under the road covered with asphalt of 5cm thickness. The pick-up modules which consist of core, winding wire, and rectifiers are fixed to the bottom of the bus which can carry more than 40 passengers and can pick up max. 60kW. To remove parasitic component and to transfer maximum power between them resonant circuit topology is applied to the primary and secondary sides. The EMF level is below 62.5mG at 1.75m from the center of the road to meet the regulation. Several effective ways of reducing EMF levels have been developed. In addition, effective ways to solve problems related high frequency power cables buried in ground and it's proof from soil have been studied also. This development shows that the IPS system is capable of supplying enough power to the pick-up of OLEV and can reduce battery size, weight and cost, which means the IPS with OLEV is one of the best candidate for EV.

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Analysis on the Safety of Structure and Economics of Replacement Method Using Rock Debris in the Soft Ground - Case Study of Miho Stream Crossing Road in Cheongju City (연약지반 암버럭 치환공법의 구조물 안정성과 경제성 분석 - 청주시 미호천 횡단도로를 대상으로)

  • Heo, Kang Kug;Park, Hyung Keun;Ahn, Byung Chul;Min, Byeong Uk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.36 no.4
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    • pp.705-713
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    • 2016
  • For the soft ground construction, the factors not considered in the design stage occurs in the construction stage so that they cause the increase of the construction cost due to the structural stability and the design change. The subject of the study is the construction section of the industrial complex access road made in the Ochang region of Chungcheongbuk-do. The study is concerned with selecting the soft ground handling method such as the replacement method using rock debris and the surcharge reflecting the service load as the soft ground handling measure and analyzing the effect of reducing the construction cost with the stability of structures and the reduction of the construction period. The soft ground in the study section consists of sandy and cohesive soil and is 2.4m to 5.5m deep. It is distributed unevenly between the 1.5m to 5.9m stratums under the ground surface. Settlement is not serious, but the future uneven settlement and difference are expected so that the future settlement behavior is estimated by analyzing the site measurement results after the soft ground treatment. Moreover, in consideration of the regional characteristics and economic efficiency, soil with good quality is replaced with rock debris as the replacement material so that 29% of the construction cost is reduced due to the increase of stability and the reduction of duration. If the estimation of the dispersion of the pore water pressure within the dam body and the change of the underground water level and the relation of the actually measured soft ground with consolidation is studied further on the basis of the study, it is expected that the behavior of the soft ground will be correctly estimated in various site conditions.

A Study on Urban Inundation Prediction Using Urban Runoff Model and Flood Inundation Model (도시유출모형과 홍수범람모형을 연계한 내수침수 적용성 평가)

  • Tak, Yong Hun;Kim, Jae Dong;Kim, Young Do;Kang, Boosik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.36 no.3
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    • pp.395-406
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    • 2016
  • Population and development are concentrated by urbanization. Consequently, the usage of underground area and the riverside area have been increased. By increasing impermeable layer, the urban basin drainage is depending on level of sewer. Flood damage is occurred by shortage of sewer capacity and poor interior drainage at river stage. Many of researches about flood stress the unavailability of connection at the river stage with the internal inundation organically. In this study, flood calculated considering rainfall and combined inland-river. Also, using urban runoff model analyze the overflow of sewer. By using results of SWMM model, using flood inundation analysis model analyzed internal drainage efficiency of drainage system. Applying SWMM model, which results to flood inundation analysis model, analyzes internal drainage efficiency of drainage system under localized heavy rain in a basin of the city. The results of SWMM model show the smoothness of internal drainage can be impossible to achieve because of the influence of the river level and sewer overflow appearing. The main manholes were selected as the manhole of a lot of overflow volume. Overflow reduction scenarios were selected for expansion of sewer conduit and instruction retention pond. Overflow volume reduces to 45% and 33~64% by retention pond instruction and sewer conduit expansion. In addition, the results of simulating of flood inundation analysis model show the flood occurrence by road runoff moving along the road slope. Flooded area reduces to 19.6%, 60.5% in sewer conduit expansion scenarios.

Analysis of the under Pavement Cavity Growth Rate using Multi-Channel GPR Equipment (멀티채널 GPR 장비를 이용한 도로하부 공동의 크기 변화 분석)

  • Park, Jeong Jun;Kim, In Dae
    • Journal of the Society of Disaster Information
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    • v.16 no.1
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    • pp.60-69
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    • 2020
  • Purpose: Cavity growth process monitoring is to periodically monitor changes in common size and topography for general and observational grades to predict the rate of common growth. The purpose of this study is to establish a systematic cavity management plan by evaluating the general and observational class community in a non-destructive method. Method: Using GPR exploration equipment, the acquired surface image and the surrounding status image are analyzed in the GPR probe radargram in depth, profile, and cross section of the location. The exact location is selected using the distance and surrounding markings shown on the road surface of the initial detection cavity, and the test cavity is analyzed by calling the radar at the corresponding location. Result: As a result of monitoring tests conducted at a cavity 30 sites of general and observation grade, nine sites have been recovered. Changes in scale were seen in 21 cavity locations, and changes in size and grade occurred in 13 locations. Conclusion: The under road cavity is caused by various causes such as damage to the burial site, poor construction, soil leakage caused by groundwater leakage, waste and ground vibration. Among them, indirect factors could infer the effects of groundwater and localized rainfall.

The Study for Utilizing Data of Cut-Slope Management System by Using Logistic Regression (로지스틱 회귀분석을 이용한 도로비탈면관리시스템 데이터 활용 검토 연구)

  • Woo, Yonghoon;Kim, Seung-Hyun;Yang, Inchul;Lee, Se-Hyeok
    • The Journal of Engineering Geology
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    • v.30 no.4
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    • pp.649-661
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    • 2020
  • Cut-slope management system (CSMS) has been investigated all slopes on the road of the whole country to evaluate risk rating of each slope. Based on this evaluation, the decision-making for maintenance can be conducted, and this procedure will be helpful to establish a consistent and efficient policy of safe road. CSMS has updated the database of all slopes annually, and this database is constructed based on a basic and detailed investigation. In the database, there are two type of data: first one is an objective data such as slopes' location, height, width, length, and information about underground and bedrock, etc; second one is subjective data, which is decided by experts based on those objective data, e.g., degree of emergency and risk, maintenance solution, etc. The purpose of this study is identifying an data application plan to utilize those CSMS data. For this purpose, logistic regression, which is a basic machine-learning method to construct a prediction model, is performed to predict a judging-type variable (i.e., subjective data) based on objective data. The constructed logistic model shows the accurate prediction, and this model can be used to judge a priority of slopes for detailed investigation. Also, it is anticipated that the prediction model can filter unusual data by comparing with a prediction value.