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<p>Automated rock mass characterization is gaining popularity in rock mechanics, particularly for determining discontinuity spacing with greater accuracy. This study employs an existing algorithm to analyze three-dimensional (3D) trace networks, focusing on the detection and clustering of discontinuity planes. In this research, the trace data are obtained via digital trace surveys on 3D models of rock outcrops, ensuring high-resolution data for analysis. Building on this foundation, a novel methodology is developed for calculating joint set spacing, accommodating a range of assumptions and scenarios. This methodology is integrated into the existing Trace Network Analyzing computer code through a graphical user interface, enabling efficient 3D trace network analysis, precise joint set identification, and accurate set spacing computation. A key innovation of this study is the introduction of co-planar plane merging within each joint set, significantly enhancing spacing estimation accuracy. Validation using a synthetic 3D model and verification via two real-world case studies demonstrates the robustness of the approach, with results showing consistent alignment with established methods. The analysis reveals that assuming non-persistent joints results in higher spacing values compared to fully persistent ones, with notable differences observed across various scenarios. The developed methodology provides a reliable tool for rock mass characterization, advancing geotechnical engineering practices by delivering improved accuracy in set spacing determination.</p>

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3D Trace Network Analysis for Improved Discontinuity Spacing Estimation in Complex Rock Formations

  • 期刊论文

  • 发表日期：

    2025年9月26日

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  • Seyedahmad Mehrishal,
  • Jineon Kim,
  • Junsu Leem,
  • Yulong Shao,
  • Jae-Joon Song

摘要

Automated rock mass characterization is gaining popularity in rock mechanics, particularly for determining discontinuity spacing with greater accuracy. This study employs an existing algorithm to analyze three-dimensional (3D) trace networks, focusing on the detection and clustering of discontinuity planes. In this research, the trace data are obtained via digital trace surveys on 3D models of rock outcrops, ensuring high-resolution data for analysis. Building on this foundation, a novel methodology is developed for calculating joint set spacing, accommodating a range of assumptions and scenarios. This methodology is integrated into the existing Trace Network Analyzing computer code through a graphical user interface, enabling efficient 3D trace network analysis, precise joint set identification, and accurate set spacing computation. A key innovation of this study is the introduction of co-planar plane merging within each joint set, significantly enhancing spacing estimation accuracy. Validation using a synthetic 3D model and verification via two real-world case studies demonstrates the robustness of the approach, with results showing consistent alignment with established methods. The analysis reveals that assuming non-persistent joints results in higher spacing values compared to fully persistent ones, with notable differences observed across various scenarios. The developed methodology provides a reliable tool for rock mass characterization, advancing geotechnical engineering practices by delivering improved accuracy in set spacing determination.