Shear instability identification method and its damage characteristics based on automatic recognition of three-dimensional curvature of limestone joint surfaces

Shi-chuan Zhang , Shi-long Song , Bao-tang Shen , Yang-yang Li

Journal of Central South University ›› 2025, Vol. 32 ›› Issue (10) : 3997 -4011.

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Journal of Central South University ›› 2025, Vol. 32 ›› Issue (10) :3997 -4011. DOI: 10.1007/s11771-025-6103-3
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Shear instability identification method and its damage characteristics based on automatic recognition of three-dimensional curvature of limestone joint surfaces

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Abstract

In deep underground engineering construction, the dominant rock failure mode, whether by tension or shear, influences the engineering instability. Therefore, the critical triggering conditions that induce shear or tensile fractures in rocks urgently need further investigation. This paper designs direct shear tests on intact limestone under different normal stress conditions, using binarization methods supplemented by scanning electron microscopy to explore the two-dimensional fracture damage characteristics of limestone joint surfaces. Based on the three-dimensional morphological characteristics of limestone joint surfaces, a method for automatically identifying the three-dimensional curvature of rock joint surfaces is proposed, quantifying the changes in curvature distribution under different normal stresses. Further analysis focused on the proportion of shear damage and high-curvature areas on the upper and lower joint surfaces of limestone. The study examined changes in the cumulative energy of pre-peak acoustic emission and damage under varying effective normal stress-to-shear stress ratios. These results were used to identify and validate the critical threshold range for inducing shear fractures in limestone. The conclusions indicate that the proportion of shear damage area of limestone joint surfaces is positively correlated with effective normal stress. The proportion of high curvature of limestone joint surfaces decreases with increasing normal stress. Both the rapid growth stage of shear damage area and the rapid descent stage of high curvature proportion occur in the effective normal stress to shear stress ratio range of [1.4, 1.6]. The cumulative energy of pre-peak acoustic emission and damage under different effective normal stress to shear stress ratios increase sharply around the ratio of 1.6, further verifying that the effective normal stress to shear stress ratio range of [1.4, 1.6] is the critical threshold range for inducing shear fractures in limestone.

Keywords

shear instability discrimination / shear damage / joint surface curvature / Otsu threshold segmentation / critical threshold

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Shi-chuan Zhang, Shi-long Song, Bao-tang Shen, Yang-yang Li. Shear instability identification method and its damage characteristics based on automatic recognition of three-dimensional curvature of limestone joint surfaces. Journal of Central South University, 2025, 32(10): 3997-4011 DOI:10.1007/s11771-025-6103-3

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References

[1]

Rong H-y, Li G-c, Zhao G-m, et al. . True triaxial test study on mechanical properties of deep rock mass in different stress paths [J]. Journal of China Coal Society, 2020, 45(9): 3140-3149(in Chinese)

[2]

Shen B-tang. Development and applications of rock fracture mechanics modelling with FRACOD: A general review [J]. Geosystem Engineering, 2014, 17(4): 235-252.

[3]

Shen B-t, Siren T, Rinne M. Modelling fracture propagation in anisotropic rock mass [J]. Rock Mechanics and Rock Engineering, 2015, 48(3): 1067-1081.

[4]

Wang C. Fracture mechanics principles of anchorage for layered rock mass slope [J]. Chinese Journal of Rock Mechanics and Engineering, 2005, 24(11): 1900-1904(in Chinese)

[5]

Meng F-z, Zhou H, Wang Z-q, et al. . Experimental study on the prediction of rockburst hazards induced by dynamic structural plane shearing in deeply buried hard rock tunnels [J]. International Journal of Rock Mechanics and Mining Sciences, 2016, 86: 210-223.

[6]

Luo Y, Huang J-c, Si X-f, et al. . An energy-based method for uniaxially compressed rocks and its implication [J]. Journal of Rock Mechanics and Geotechnical Engineering, 2025, 17(3): 1429-1444.

[7]

Si X-f, Luo Y, Gong F-q, et al. . Temperature effect of rockburst in granite Caverns: Insights from reduced-scale model true-triaxial test [J]. Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 2024, 10(1): 26.

[8]

Sainoki A, Mitri H S. Dynamic behaviour of mining-induced fault slip [J]. International Journal of Rock Mechanics and Mining Sciences, 2014, 66: 19-29.

[9]

Barton N, Bandis S, Bakhtar K. Strength, deformation and conductivity coupling of rock joints [J]. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 1985, 22(3): 121-140.

[10]

Olsson R, Barton N. An improved model for hydromechanical coupling during shearing of rock joints [J]. International Journal of Rock Mechanics and Mining Sciences, 2001, 38(3): 317-329.

[11]

Indraratna B, Haque A. Experimental study of shear behavior of rock joints under constant normal stiffness conditions [J]. International Journal of Rock Mechanics and Mining Sciences, 1997, 34(3–4): 141.e1-141.e14

[12]

Grasselli G, Wirth J, Egger P. Quantitative three-dimensional description of a rough surface and parameter evolution with shearing [J]. International Journal of Rock Mechanics and Mining Sciences, 2002, 39(6): 789-800.

[13]

Grasselli G, Egger P. Constitutive law for the shear strength of rock joints based on three-dimensional surface parameters [J]. International Journal of Rock Mechanics and Mining Sciences, 2003, 40(1): 25-40.

[14]

Chen X, Zeng Y-wu. A new three-dimensional roughness metric based on Grasselli’s model [J]. Rock and Soil Mechanics, 2021, 42(3): 700-712

[15]

CAO Ping, JIA Hong-qiang, LIU Tao-ying, et al. Fractal analysis of three-dimensional morphological characteristics of rock joint surface [J]. Chinese Journal of Rock Mechanics and Engineering, 2011(S2): 3839–3843. (in Chinese)

[16]

Rao Q-h, Sun Z-q, Liu h-l, et al. . Determination of rock shear fracture toughness KIIC under shear box loading [J]. Journal of Central South University of Technology, 2001, 6: 563-567

[17]

Sun Z-q, Rao Q-h, Wang G-yao. Research on the determination of shear fracture toughness KIIC [J]. Chinese Journal of Rock Mechanics and Engineering, 2002, 02: 199-203.

[18]

Liu D-q, Sun J, Zhang L, et al. . Classification method of rock tensile and shear cracks and its application in rockburst precursors [J]. Journal of Central South University (Natural Science), 2023, 54(3): 1153-1167(in Chinese)

[19]

Liu J-p, Liu Z-s, Wang S-q, et al. . Analysis of acoustic emission source mechanisms for tensile and shear cracks of rock fractures [J]. Journal of Northeastern University (Natural Science), 2015, 36(11): 1624-1628(in Chinese)

[20]

Li X-j, Chen J-q, Zhu H-hua. A new method for automated discontinuity trace mapping on rock mass 3D surface model [J]. Computers & Geosciences, 2016, 89: 118-131.

[21]

Umili G, Ferrero A, Einstein H H. A new method for automatic discontinuity traces sampling on rock mass 3D model [J]. Computers & Geosciences, 2013, 51: 182-192.

[22]

Yi X-y, Feng W-k, Wang D, et al. . An efficient method for extracting and clustering rock mass discontinuities from 3D point clouds [J]. Acta Geotechnica, 2023, 18(7): 3485-3503.

[23]

Wang X, Zou L-j, Shen X-h, et al. . A region-growing approach for automatic outcrop fracture extraction from a three-dimensional point cloud [J]. Computers & Geosciences, 2017, 99: 100-106.

[24]

Thiele S T, Grose L, Samsu A, et al. . Rapid, semiautomatic fracture and contact mapping for point clouds, images and geophysical data [J]. Solid Earth, 2017, 8(6): 1241-1253.

[25]

Li Q, Zhao G-f, Lian J-jian. A fundamental investigation of the tensile failure of rock using the three-dimensional lattice spring model [J]. Rock Mechanics and Rock Engineering, 2019, 52(7): 2319-2334.

[26]

Li X-z, Xia C, Qi C-z, et al. . Dynamic localized shear failure influenced by changing rates in brittle solids containing initial microcracks [J]. International Journal of Impact Engineering, 2020, 135: 103408.

[27]

Laubach S E, Lamarche J, Gauthier B D M, et al. . Spatial arrangement of faults and opening-mode fractures [J]. Journal of Structural Geology, 2018, 108: 2-15.

[28]

Kluge C, Blöcher G, Barnhoorn A, et al. . Permeability evolution during shear zone initiation in low-porosity rocks [J]. Rock Mechanics and Rock Engineering, 2021, 54(10): 5221-5244.

[29]

Siman-Tov S, Aharonov E, Sagy A, et al. . Nanograins form carbonate fault mirrors [J]. Geology, 2013, 41(6): 703-706.

[30]

Fondriest M, Smith S A F, Candela T, et al. . Mirrorlike faults and power dissipation during earthquakes [J]. Geology, 2013, 41(11): 1175-1178.

[31]

Verberne B A, Spiers C J, Niemeijer A R, et al. . Frictional properties and microstructure of calcite-rich fault gouges sheared at sub-seismic sliding velocities [J]. Pure and Applied Geophysics, 2014, 171(10): 2617-2640.

[32]

Maiti A, Choudhary A, Chakravarty D. A k-means clustering – based approach for 3D mapping and characterization of rock faces using digital images [J]. Arabian Journal of Geosciences, 2021, 14(10): 848.

[33]

Zhan J-w, Chen J-p, Xu P-h, et al. . Automatic identification of rock fracture sets using finite mixture models [J]. Mathematical Geosciences, 2017, 49(8): 1021-1056.

[34]

Chen N, Wu X-c, Xiao H-l, et al. . Semiautomatic recognition of rock mass discontinuity based on 3D point clouds. Discover Applied Sciences, 2024, 6(5): 230.

[35]

Otsu N. A threshold selection method from gray-level histograms [J]. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1): 62-66.

[36]

Pemula R, Raju C. The optimal thresholding technique for image segmentation using fuzzy Otsu method [J]. International Journal of Applied Engineering Research, 2015, 10(13): 33842-33846

[37]

Sha C-s, Hou J, Cui H-xia. A robust 2D Otsu’s thresholding method in image segmentation [J]. Journal of Visual Communication and Image Representation, 2016, 41: 339-351.

[38]

Nakib A, Roman S, Oulhadj H, et al. . Fast brain MRI segmentation based on two-dimensional survival exponential entropy and particle swarm optimization [C]. 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, Lyon, France. IEEE5563-5566.

[39]

HUAN Jiu-yang, ZHANG Zhi-qiang, LI Ning. Particle flow simulation of staggered joint rock by direct shear tests [J]. Hydro-Science and Engineering, 2018(4): 9–17. DOI: https://doi.org/10.16198/j.cnki.1009-640X.2018.04.002.

[40]

Yang Z-p, Li J, Jiang Y-w, et al. . Influences of stone content on shear mechanical properties of soil-rock mixture-bedrock interface [J]. Chinese Journal of Geotechnical Engineering, 2021, 43(8): 1443-14523

[41]

Han X-x, Zhang S-c, Shen B-t, et al. . Shear crack propagation laws and fracture mechanism of filled joint granite with different angles [J]. Journal of Shandong University of Science and Technology (Natural Science), 2024, 43(2): 13-21(in Chinese)

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