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Characterization and clustering of rock discontinuity sets: A review
The characterization and clustering of rock discontinuity sets are a crucial and challenging task in rock mechanics and geotechnical engineering. Over the past few decades, the clustering of discontinuity sets has undergone rapid and remarkable development. However, there is no relevant literature summarizing these achievements, and this paper attempts to elaborate on the current status and prospects in this field. Specifically, this review aims to discuss the development process of clustering methods for discontinuity sets and the state-of-the-art relevant algorithms. First, we introduce the importance of discontinuity clustering analysis and follow the comprehensive characterization approaches of discontinuity data. A bibliometric analysis is subsequently conducted to clarify the current status and development characteristics of the clustering of discontinuity sets. The methods for the clustering analysis of rock discontinuities are reviewed in terms of single- and multi-parameter clustering methods. Single-parameter methods can be classified into empirical judgment methods, dynamic clustering methods, relative static clustering methods, and static clustering methods, reflecting the continuous optimization and improvement of clustering algorithms. Moreover, this paper compares the current mainstream of single-parameter clustering methods with multi-parameter clustering methods. It is emphasized that the current single-parameter clustering methods have reached their performance limits, with little room for improvement, and that there is a need to extend the study of multi-parameter clustering methods. Finally, several suggestions are offered for future research on the clustering of discontinuity sets.
Characterization and clustering of rock discontinuity sets: A review
The characterization and clustering of rock discontinuity sets are a crucial and challenging task in rock mechanics and geotechnical engineering. Over the past few decades, the clustering of discontinuity sets has undergone rapid and remarkable development. However, there is no relevant literature summarizing these achievements, and this paper attempts to elaborate on the current status and prospects in this field. Specifically, this review aims to discuss the development process of clustering methods for discontinuity sets and the state-of-the-art relevant algorithms. First, we introduce the importance of discontinuity clustering analysis and follow the comprehensive characterization approaches of discontinuity data. A bibliometric analysis is subsequently conducted to clarify the current status and development characteristics of the clustering of discontinuity sets. The methods for the clustering analysis of rock discontinuities are reviewed in terms of single- and multi-parameter clustering methods. Single-parameter methods can be classified into empirical judgment methods, dynamic clustering methods, relative static clustering methods, and static clustering methods, reflecting the continuous optimization and improvement of clustering algorithms. Moreover, this paper compares the current mainstream of single-parameter clustering methods with multi-parameter clustering methods. It is emphasized that the current single-parameter clustering methods have reached their performance limits, with little room for improvement, and that there is a need to extend the study of multi-parameter clustering methods. Finally, several suggestions are offered for future research on the clustering of discontinuity sets.
Characterization and clustering of rock discontinuity sets: A review
Changle Pu (author) / Jiewei Zhan (author) / Wen Zhang (author) / Jianbing Peng (author)
2025
Article (Journal)
Electronic Resource
Unknown
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