• Title/Summary/Keyword: Underground Facility Operations

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Capabilities Required for Underground Facility Operations in Korean Megacities (한국 메가시티 지하시설 작전에 요구되는 능력)

  • Jun Hak Sim;Seung Jin Jo;Jun Woo Kim;Ji Woong Choi;Won Jun Choi;Sun Il Yang;Sang Hyuk Park
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.267-272
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    • 2024
  • Recently, major advanced countries are fostering megacities through policy for reasons such as solving population problems, political and economic issues, and strengthening national competitiveness. The trend of change is accelerating. In Korea, following Seoul and Gyeonggi, mega city policies are being promoted in Busan, Ulsan, Gyeongnam, Daegu and Gyeongbuk, Gwangju and Jeonnam, and Daejeon, Sejong, South Chungcheong and North Chungcheong areas. Due to this urbanization phenomenon, military experts predict that the future battlefield environment will be space or a large city (mega city). From this perspective, Korea will not be able to effectively respond to the threats facing megacities if it does not prepare in advance. Therefore, underground facility operation capabilities optimized for the huge scale of the mega city and the characteristics of the underground operational environment are required. Against this background, the characteristics of the underground operational environment of mega cities and cases of preparation for underground facility operations in advanced military countries such as the United States and Israel were analyzed. Based on this, the capabilities required for underground facility operations suitable for the underground operational environment within Korean megacities are developed from an idea perspective to military organization and combat system, securing special equipment and materials to ensure combatant survival, developing small unit combat techniques, and establishing a training system. It was presented with priority given to.

Implementation of a Modified SQI for the Preprocessing of Magnetic Flux Leakage Signal

  • Oh, Bok-Jin;Choi, Doo-Hyun
    • Journal of Magnetics
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    • v.18 no.3
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    • pp.357-360
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    • 2013
  • A modified SQI method using magnetic leakage flux (MFL) signal for underground gas pipelines' defect detection and characterization is presented in this paper. Raw signals gathered using MFL signals include many unexpected noises and high frequency signals, uneven background signals, signals caused by real defects, etc. The MFL signals of defect free pipelines primarily consist of two kinds of signals, uneven low frequency signals and uncertain high frequency noises. Leakage flux signals caused by defects are added to the case of pipelines having defects. Even though the SQI (Self Quotient Image) is a useful tool to gradually remove the varying backgrounds as well as to characterize the defects, it uses the division and floating point operations. A modified SQI having low computational complexity without time-consuming division operations is presented in this paper. By using defects carved in real pipelines in the pipeline simulation facility (PSF) and real MFL data, the performance of the proposed method is compared with that of the original SQI.

The French Underground Research Laboratory in Bure: An Essential Tool for the Development and Preparation of the French Deep Geological Disposal Facility Cigéo

  • Pascal Claude LEVERD
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.21 no.4
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    • pp.489-502
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    • 2023
  • This article presents the crucial role played by the French underground research laboratory (URL) in initiating the deep geological repository project Cigéo. In January 2023, Andra finalized the license application for the initial construction of Cigéo. Depending on Government's decision, the construction of Cigéo may be authorized around 2027. Cigéo is the result of a National program, launched in 1991, aiming to safely manage high-level and intermediate level long-lived radioactive wastes. This National program is based on four principles: 1) excellent science and technical knowledge, 2) safety and security as primary goals for waste management, 3) high requirements for environment protection, 4) transparent and open-public exchanges preceding the democratic decisions and orientations by the Parliament. The research and development (R&D) activities carried out in the URL supported the design and the safety demonstration of the Cigéo project. Moreover, running the URL has provided an opportunity to gain practical experience with regard to the security of underground operations, assessment of environmental impacts, and involvement of the public in the preparation of decisions. The practices implemented have helped gradually build confidence in the Cigéo project.

Crack detection in concrete using deep learning for underground facility safety inspection (지하시설물 안전점검을 위한 딥러닝 기반 콘크리트 균열 검출)

  • Eui-Ik Jeon;Impyeong Lee;Donggyou Kim
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.6
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    • pp.555-567
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    • 2023
  • The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.

Wireless sensor network analysis of suitable types for fixed facility surveillance (고정설비감시를 위한 무선센서네트워크 형태 분석)

  • Lee, Hoo-Rock;Rhyu, Keel-Soo;Chung, Kyung-Yul
    • Journal of Advanced Marine Engineering and Technology
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    • v.40 no.1
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    • pp.50-54
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    • 2016
  • A Wireless Sensor Network (WSN) is better than a conventional network for use in construction and Operations and Maintenance (O&M) because of its lower surveillance system cost. However, effective operation of a WSN is often difficult to obtain because the surveillance targets are usually fixed inside the building or underground. Therefore, this environmental constraint should be considered in the design of the WSN plant equipment surveillance system prior to installation. This study employs simulations of WSN-based fixed facility surveillance using the TinyOS TOSSIM simulator to investigate ideal types and setups of the WSN. Simulation target protocols included LEACH and flooding and gossiping protocols. The results show that the hierarchically-structured LEACH protocol demonstrated better load-balancing and efficiency than the flatly-structured flooding and gossiping protocol.