Development of an Automatic Rock Mass Classification System Using Digital Tunnel Face Mapping

To mitigate unforeseen incidents, such as key block failure or tunnel collapse during excavation, an appropriate support pattern that correlates with the geological conditions of the rock mass at the tunnel face should be designed. Rock mass evaluations should be conducted through geological face mapping during the construction phase, alongside predictions based on field investigations during the design phase. When marked discrepancies are identified, it is customary to convene an on-site evaluation involving a committee of experts. This study develops a digital tunnel face mapping system that utilises mobile devices to facilitate online evaluations during the construction phase. This system effectively replaces the traditional on-site field evaluation method. Tunnel face mapping can be promptly accomplished using images captured at the excavation face, enabling rapid analysis. In conjunction with the mapping capabilities, the developed system was designed to digitally store geological information, which includes parameters such as rock strength distribution, the spacing and length of discontinuities observed during the mapping process, as well as data pertaining to weathering and the groundwater conditions of those discontinuities. This information was then correlated with the rock mass rating sheet to automate the determination of ratings for each parameter, ultimately leading to a conclusive classification of the rock mass quality. By employing this system for tunnel face mapping and rock quality evaluation, we significantly reduced the discrepancies in the evaluation results that often arise due to the subjective judgement of geologists, as well as human errors that can occur throughout the rating process.

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Publication Details

Journal
Applied Sciences
Published
2024-10-06
DOI
https://doi.org/10.3390/app14199024
Citations
1
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.27

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article

Development of an Automatic Rock Mass Classification System Using Digital Tunnel Face Mapping

Myung Kyu Song, Sean Seungwon Lee, Hyun-Koo Lee, Young-Oh Jeong
1 citations
Applied Sciences
Rock Mechanics and Modeling
0.27
article

Development of an Automatic Rock Mass Classification System Using Digital Tunnel Face Mapping

Myung Kyu Song, Sean Seungwon Lee, Hyun-Koo Lee, Young-Oh Jeong
article en
1 citations

Abstract

To mitigate unforeseen incidents, such as key block failure or tunnel collapse during excavation, an appropriate support pattern that correlates with the geological conditions of the rock mass at the tunnel face should be designed. Rock mass evaluations should be conducted through geological face mapping during the construction phase, alongside predictions based on field investigations during the design phase. When marked discrepancies are identified, it is customary to convene an on-site evaluation involving a committee of experts. This study develops a digital tunnel face mapping system that utilises mobile devices to facilitate online evaluations during the construction phase. This system effectively replaces the traditional on-site field evaluation method. Tunnel face mapping can be promptly accomplished using images captured at the excavation face, enabling rapid analysis. In conjunction with the mapping capabilities, the developed system was designed to digitally store geological information, which includes parameters such as rock strength distribution, the spacing and length of discontinuities observed during the mapping process, as well as data pertaining to weathering and the groundwater conditions of those discontinuities. This information was then correlated with the rock mass rating sheet to automate the determination of ratings for each parameter, ultimately leading to a conclusive classification of the rock mass quality. By employing this system for tunnel face mapping and rock quality evaluation, we significantly reduced the discrepancies in the evaluation results that often arise due to the subjective judgement of geologists, as well as human errors that can occur throughout the rating process.

Applied SciencesVol. 14(19)
Hanyang University (KR), Anyang University (KR)
Ministry of Land, Infrastructure and Transport, Korea Agency for Infrastructure Technology Advancement
Sustainable cities and communities
Openalex Percentile: Top 50%
Rock Mechanics and Modeling
0.27
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