A Critical Discussion on the Use of Discrete Fracture Network Models in Rock Engineering Practice: Why Rock Mass Characterisation Methods can Benefit from Considering Fracture Connectivity.

Fracture connectivity refers to the degree to which fractures within a rock mass are spatially arranged and interconnected. As a result, fracture connectivity can affect the pattern and magnitude of deformations, and induced brittle damage in response to external forces. Traditionally, fracture intensity has been a standard metric for characterising rock mass quality. This paper explains why fracture connectivity should be included in addition to fracture intensity as a characterisation parameter. Fracture intensity alone cannot capture the complex interactions and pathways that fractures create within the rock mass. On the other hand, fracture connectivity offers a more comprehensive view of how fractures propagate and interact, enabling a deeper understanding of stress transfer and deformation patterns. This paper reviews the Network Connectivity Index (NCI) and its applications in rock engineering design. It is discussed that NCI, considering both fracture intensity and fracture connectivity, serves as a more objective measurement to reduce the degree of subjectivity of many empirical methods. Furthermore, an extensive set of DFN models suggests that NCI correlates better with block sizes and can serve as a more representative parameter than P32\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${P}_{32}$$\end{document} for fragmentation assessment in cave mine design.Fracture connectivity can affect the pattern and magnitude of deformations and induce brittle damage in response to external forces.Fracture intensity has limitations in capturing the complex interactions and pathways that fractures create within the rock mass.Fracture connectivity offers additional information as to how fractures propagate and interact.The Network Connectivity Index (NCI) is a novel and objective measurement that can be easily extracted from discrete fracture network models.NCI correlates better with block sizes and can serve as a more representative parameter than P32 for fragmentation assessment in cave mine design.Fracture connectivity can affect the pattern and magnitude of deformations and induce brittle damage in response to external forces.Fracture intensity has limitations in capturing the complex interactions and pathways that fractures create within the rock mass.Fracture connectivity offers additional information as to how fractures propagate and interact.The Network Connectivity Index (NCI) is a novel and objective measurement that can be easily extracted from discrete fracture network models.NCI correlates better with block sizes and can serve as a more representative parameter than P32 for fragmentation assessment in cave mine design.Highlights: Fracture connectivity refers to the degree to which fractures within a rock mass are spatially arranged and interconnected. As a result, fracture connectivity can affect the pattern and magnitude of deformations, and induced brittle damage in response to external forces. Traditionally, fracture intensity has been a standard metric for characterising rock mass quality. This paper explains why fracture connectivity should be included in addition to fracture intensity as a characterisation parameter. Fracture intensity alone cannot capture the complex interactions and pathways that fractures create within the rock mass. On the other hand, fracture connectivity offers a more comprehensive view of how fractures propagate and interact, enabling a deeper understanding of stress transfer and deformation patterns. This paper reviews the Network Connectivity Index (NCI) and its applications in rock engineering design. It is discussed that NCI, considering both fracture intensity and fracture connectivity, serves as a more objective measurement to reduce the degree of subjectivity of many empirical methods. Furthermore, an extensive set of DFN models suggests that NCI correlates better with block sizes and can serve as a more representative parameter than P32\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${P}_{32}$$\end{document} for fragmentation assessment in cave mine design.Fracture connectivity can affect the pattern and magnitude of deformations and induce brittle damage in response to external forces.Fracture intensity has limitations in capturing the complex interactions and pathways that fractures create within the rock mass.Fracture connectivity offers additional information as to how fractures propagate and interact.The Network Connectivity Index (NCI) is a novel and objective measurement that can be easily extracted from discrete fracture network models.NCI correlates better with block sizes and can serve as a more representative parameter than P32 for fragmentation assessment in cave mine design.Fracture connectivity can affect the pattern and magnitude of deformations and induce brittle damage in response to external forces.Fracture intensity has limitations in capturing the complex interactions and pathways that fractures create within the rock mass.Fracture connectivity offers additional information as to how fractures propagate and interact.The Network Connectivity Index (NCI) is a novel and objective measurement that can be easily extracted from discrete fracture network models.NCI correlates better with block sizes and can serve as a more representative parameter than P32 for fragmentation assessment in cave mine design. [ABSTRACT FROM AUTHOR]