A method for clustering rock discontinuities with multiple properties based on an improved netting algorithm

Abstract Clustering analysis is fundamental for determining dominant discontinuity properties in rock engineering. Orientation has commonly been considered the only factor when performing clustering, which ignores contributions of other to deformations and strengths masses. This study proposes an improved netting algorithm identify sets based on multiple properties. The method takes ten as clustering factors: dip direction, dip, trace length, spacing, aperture, infilling material, percentage, roughness, water permeability, strength. Meanwhile, a novel weighting used weigh each property combines advantages subjective objective methods. validity proposed tested using artificial data Monte Carlo situ from relevant literature. results indicate that can effectively filter noise data, rejection rate approximately 26%. initial number centers are not necessary, facilitates achieving global optimization. Finally, open-pit mine slope Xinjiang Province, China, case illustrate utility method. new potentially useful tool rapidly obtain