• Title/Summary/Keyword: 심발공

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The Method of Tunnel Blasting for the Vibration Control by Deck Charge and Multiple Cut (다단장약에 의한 V-cut 발파공법의 진동제어효과와 발파효율증대에 관한 연구)

  • 두준기;양형식;김형건;김용국
    • Explosives and Blasting
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    • v.21 no.3
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    • pp.1-10
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    • 2003
  • 터널굴착발파공법의 하나인 V-cut발파공법은 터널굴착기술이 발전되는 과정에서 초기에 개발되어진 기술이나 작업의 간편성과 효율성으로 인하여 많은 터널굴착공사에서 이용되고 있는 발파공법이다. V-cut발파공법은 일자유면 상태에서 V형으로 심발공을 발파하고 심발공에 의해 형성된 자유면을 이용하여 확대공으로 굴착공간을 넓히는 발파 방법이며 심발발파의 굴진장에 의해 단일발파당 굴진장이 결정된다. V-cut발파법이 개발된 이래 V-cut발파의 굴진장을 증대시키기 위한 방법으로 심발발파공의 구속저항을 감소시키기 위해 보조심발공을 발파하여 형성된 자유면에 의해 심발공의 최소저항선거리를 줄여 발파하였으나 심발공의 구속저항이 감소되지 않아 발파효율이 증대되지 않았으며 발파진동 또한 가장 크게 발생하였다. 이와 같은 현상은 최소저항선거리의 감소효과에 대한 발파기술상의 이론에 문제가 있기 때문이다. 본 연구에서는 V-cut발파법의 심발공에 대한 구속저항감소효과가 발현될 수 있는 조건들을 검토하여 최소저항선거리의 감소효과가 발현될 수 있는 조건을 제시 하여 심발공의 발파효율을 증대시키고 발파진동이 적어지는 발파방법을 제안하려 한다.

Development and Application of Large-diameter Cut-hole Exploration System for Assessment of the Geological Condition beyond NATM Tunnel Face (NATM 터널의 굴착면 전방 지질 평가를 위한 대구경 심발공 탐사 시스템 개발 및 적용 사례)

  • Kim, Minseong;Jung, Jinhyeok;Lee, Jekyum;Park, Minsun;Bak, Jeonghyeon;Lee, Sean Seungwon
    • Tunnel and Underground Space
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    • v.31 no.1
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    • pp.1-9
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    • 2021
  • Recently, the development of underground space has been accelerated with rapid urbanization, and it is significantly important for safe construction to accurately understand the geological conditions of the section when excavating rocks. In this paper, a boring alignment tracking and geological exploration system have been developed to identify the geological conditions beyond the excavation face by utilizing a MSP method that bores a large empty hole to reduce blast-induced vibration. The major advantage of the proposed exploration system is that we can obtain the ground condition of 50 m ahead of the excavation face through exploration along blast cut-holes drilled for the NATM tunnel construction. In addition, we introduce several case histories regarding the assessment of the geological conditions beyond the tunnel face by monitoring the inside of large empty holes using the proposed hole exploration system.

A Study on the Effect of Artificial Cutting Slot on the Fragmentation and Vibration Propagation in the Full-scaled Concrete Block Blasting (콘크리트 블록 발파 실험을 통한 인공 슬롯 자유면이 진동전파 및 파쇄효과에 미치는 영향에 관한 연구)

  • Oh, Se-Wook;Min, Gyeong-Jo;Park, Se-Woong;Park, Hoon;Noh, You-Song;Suk, Chul-Gi;Cho, Sang-Ho
    • Tunnel and Underground Space
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    • v.28 no.6
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    • pp.692-705
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    • 2018
  • Ground vibration is one of the remarkable issues in tunnel blasting. In recent studies, to improve the fragmentation with reduction of ground vibration in tunnel blasting, a vibration-controlled blasting method with artificial cutting slot near the center-cut holes has been suggested. This study examines the effect of the different arrangement of artificial cut-slot on the vibration reduction and fragmentation by performing the full-scaled concrete block blast experiments and the numerical simulations with 3D-DFPA. The results show that the existence of artificial slot contributes to the improvement of vibration reduction, blast fragmentation and the efficiency of the cutting slot blast. It can be explained that the artificial slot play a free surface role and should decrease the burden between the cut holes. Crater volumes of the blasted concrete blocks were measured by 3-dimensional digital image analysis and compared with the ideal standard crater volume which can be calculated by theoretical standard blast design method. As a result, the ratio of burden and hole diameter which should achieve the standard crater in the cut-hole blasting were suggested.

A Study on the Decay Effect of Ground Vibration based on the Number of PLHBM Holes in Gneiss Area (편마암지역에서 선대구경 수평보링 공수적용에 따른 지반진동 감쇠효과 연구)

  • Choi, Hyung-Bin;Han, Dong-Hun;Ki, Kyung-Chul
    • Explosives and Blasting
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    • v.34 no.2
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    • pp.1-9
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    • 2016
  • In this study, the field tests were performed on V-cut, PLHBM 1 hole, PLHBM 2 hole in gneiss area in order to compare the effects of the vibration decay of a tunnel cut-hole according to the number of PLHBM holes with scaled distance. Based on the prediction equation of blasting vibration from the result of the tests, the decay rate of vibration were confirmed 21.8~61.1% using PLHBM 1 hole, 35.7~79.3% using PLHBM 2 hole for scaled distance within $10{\sim}100m/kg^{1/2}$ on the basis of V-cut PPV. As the scaled distance was increased, the effect of vibration decay was decreased. The effect of vibration decay of cut-hole for intial PLHBM 1~2 hole was significantly high.

A fundamental study on the automation of tunnel blasting design using a machine learning model (머신러닝을 이용한 터널발파설계 자동화를 위한 기초연구)

  • Kim, Yangkyun;Lee, Je-Kyum;Lee, Sean Seungwon
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.24 no.5
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    • pp.431-449
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    • 2022
  • As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.