Advancing Blast Fragmentation Assessment Using Geotechnical Discontinuity Analysis Within a Unified WipFrag Framework

Understanding rock mass structural features is essential for optimizing blast design, highwall control, and evaluating post-blast performance in both surface and underground mining operations. This paper presents a comprehensive methodology utilizing image-based structural mapping to accurately characterize geological discontinuities including joints, faults, and lineations captured from both terrestrial and aerial imagery at varying scales. Key structural parameters such as joint orientation, spacing, and apparent in-situ block size are extracted to understand rock mass classification and enhance blast design inputs with greater geotechnical precision. The study introduces a significant enhancement to the existing discontinuity assessment algorithm by integrating a deep learning-assisted detection process. This improvement enables more accurate, quantitative and consistent identification of pre-existing cracks and surface features across complex bench free faces. The enhanced system facilitates better evaluation of how structural features influence blast fragmentation, energy distribution, and slope stability. A case study from a limestone quarry illustrates the use of a derived comminution factor based on the relationship between joint-controlled pre-blast block sizes and post-blast fragmentation to evaluate blast performance and optimize future design strategies. The results highlight the value of structural analysis in reducing overbreak, minimizing underbreak, and improving fragmentation predictability. This paper emphasizes the importance of integrating structural assessments into the blasting workflow to enable a more data-driven, geotechnically informed, and performance-optimized approach to modern blast design and evaluation.