Technical Papers
Jul 5, 2023

Relationship between Local Deformation and Global Stability of Rock Using the Global–Local Dissipation Energy Time-Series Variation Coefficient

Publication: International Journal of Geomechanics
Volume 23, Issue 9

Abstract

The tension and slide of surrounding rock are highly inclined to cause dynamic disasters, thus seriously threatening the safety of mine resource recovery. This study proposes a novel method based on the global–local dissipation energy time-series variation coefficient in order to analyze the relationship between local deformation and global stability of rock. The localized light-force monitoring test method is used to analyze the tensile-sliding effect, and the evolution characteristics of the global–local dissipative energy time-series variation coefficient are compared. The results indicate that the strength reduction of rock is affected by the deformation accumulation of the loading displacement field. As for the stable damage specimen, the sliding displacement occurs 5.5 s earlier than tensile displacement, which is 4.4 s longer than the case of the transient damage specimen. The node spring model theory is further proposed to determine whether the global–local dissipation energy relationship of rock under load conformed to the linear function distribution. The global–local dissipation energy time-series variation coefficient range is always in the [1, 0.9] range. Rock instability can be predicted based on the slope and inflection point changes in the time-series variation coefficient curve, and increasing the number of effective monitoring points can significantly improve the monitoring effect and accuracy of the local time-series variation coefficient.

Practical Applications

As an important component of safe mining space, the roadway surrounding rock is prone to instability due to tensile and sliding failure, which seriously affects the safe and efficient mining of mine resources. Based on global–local energy, a new method of time-series variation coefficient is proposed in this study according to the local tensile and sliding deformation tests. By fitting the rock global–local energy relationship, the internal relationship between the local time-series variation index and the overall stability is determined. The result shows that the point measurement data in practical application are almost invariably local information because the rock deformation and stress data monitored in the roadway surrounding rock are almost reflected in the form of measuring points. Therefore, it is crucial to study the feedback of the local time-series variation coefficient on global stability, which provides an important index for early warnings of surrounding rock instability and failure. Meanwhile, it also points the direction for further improving the rock stability control theory in rock mechanics.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

This work was supported by the National Key R&D Program Funding Project (2021YFC3001301), The Fundamental Research Funds for the Central Universities (Project Number: FRF-TP-19-009B1), and The National Youth Talent Support Program (SQ2022QB03353).

References

Antoš, J., V. Nežerka, and M. Somr. 2019. “Real-time optical measurement of displacements using subpixel image registration.” Exp. Tech. 43 (3): 315–323. https://doi.org/10.1007/s40799-019-00315-1.
Aslam, M. 2019. “A new method to analyze rock joint roughness coefficient based on neutrosophic statistics.” Measurement 146: 65–71. https://doi.org/10.1016/j.measurement.2019.06.024.
Bai, Q.-S., S.-H. Tu, M. Chen, and C. Zhang. 2016. “Numerical modeling of coal wall spall in a longwall face.” Int. J. Rock Mech. Min. Sci. 88: 242–253. https://doi.org/10.1016/j.ijrmms.2016.07.031.
Bastola, S., and M. Cai. 2020. “Investigation of mechanical properties of jointed granite under compression using lattice-spring-based synthetic rock mass modeling approach.” Int. J. Rock Mech. Min. Sci. 126: 104191. https://doi.org/10.1016/j.ijrmms.2019.104191.
Cao, Y., Z. Jiao, Y. Zhen, F. Li, and G. Wu. 2022. “A reconstruction method to determine crack length based on virtual extensometers.” Eng. Fract. Mech. 264: 108337. https://doi.org/10.1016/j.engfracmech.2022.108337.
Chen, Y. 2018. “Permeability evolution in granite under compressive stress condition.” Geotech. Geol. Eng. 36 (1): 641–647. https://doi.org/10.1007/s10706-017-0313-x.
Dautriat, J., M. Bornert, N. Gland, A. Dimanov, and J. Raphanel. 2011. “Localized deformation induced by heterogeneities in porous carbonate analysed by multi-scale digital image correlation.” Tectonophysics 503 (1–2): 100–116. https://doi.org/10.1016/j.tecto.2010.09.025.
Deng, S., J. Li, H. Jiang, and M. Wang. 2018. “Experimental and theoretical study of the fault slip events of rock masses around underground tunnels induced by external disturbances.” Eng. Geol. 233: 191–199. https://doi.org/10.1016/j.enggeo.2017.12.007.
Gao, G., W. Yao, K. Xia, and Z. Li. 2015. “Investigation of the rate dependence of fracture propagation in rocks using digital image correlation (DIC) method.” Eng. Fract. Mech. 138: 146–155. https://doi.org/10.1016/j.engfracmech.2015.02.021.
Gu, C., Q. Xu, H. Yang, X. Fang, and G. Xue. 2021. “Asymmetric deformation mechanism and control of roadway in structural complex area.” Geotech. Geol. Eng. 39 (1): 145–155. https://doi.org/10.1007/s10706-020-01479-z.
Hedayat, A., H. Haeri, J. Hinton, H. Masoumi, and G. Spagnoli. 2018. “Geophysical signatures of shear-induced damage and frictional processes on rock joints.” J. Geophys. Res. Solid Earth 123 (2): 1143–1160. https://doi.org/10.1002/2017JB014773.
Hou, D., X. Fu, and C. Lu. 2021. “Research on failure process and precursor information of surrounding rock of deep layered roadway based on digital image correlation method.” Geotech. Geol. Eng. 39 (7): 4817–4831. https://doi.org/10.1007/s10706-021-01795-y.
Huang, M., C. Hong, C. Ma, Z. Luo, and S. Du. 2020. “Characterization of rock joint surface anisotropy considering the contribution ratios of undulations in different directions.” Sci. Rep. 10 (1): 17117. https://doi.org/10.1038/s41598-020-74229-z.
Ivković, I., and V. Rajić. 2021. “Better confidence intervals for the population coefficient of variation.” Commun. Stat. – Simul. Comput. 50 (12): 4215–4262. https://doi.org/10.1080/03610918.2019.1642482.
Jian-po, L., L. Yuan-hui, and X. Shi-da. 2018. “Relationship between microseismic activities and mining parameters during deep mining process.” J. Appl. Geophys. 159: 814–823. https://doi.org/10.1016/j.jappgeo.2018.10.018.
Lenoir, N., M. Bornert, J. Desrues, P. Bésuelle, and G. Viggiani. 2007. “Volumetric digital image correlation applied to X-ray microtomography images from triaxial compression tests on argillaceous rock.” Strain 43 (3): 193–205. https://doi.org/10.1111/j.1475-1305.2007.00348.x.
Li, G., S. Qin, P. Li, M. Wang, and X. Wu. 2016. “New models to predict rock failure by linking the volume dilatant point with the peak stress point.” Arabian J. Geosci. 9 (14): 647. https://doi.org/10.1007/s12517-016-2669-2.
Li, Q., G.-F. Zhao, and J. Lian. 2019. “A fundamental investigation of the tensile failure of rock using the three-dimensional lattice spring model.” Rock Mech. Rock Eng. 52 (7): 2319–2334. https://doi.org/10.1007/s00603-018-1702-z.
Liu, G.-J., H. Zhang, Y.-W. Zhu, W.-H. Cao, X.-J. Ji, C.-P. Lu, and Y. Liu. 2021. “Investigations of coal–rock parting-coal structure (CRCS) slip and instability by excavation.” Shock Vib. 2021: 1–15. https://doi.org/10.1155/2021/1715644.
Liu, Y., C. He, S. Wang, Y. Peng, and Y. Lei. 2020. “Dynamic splitting tensile properties and failure mechanism of layered slate.” Adv. Civ. Eng. 2020: 1–16. https://doi.org/10.1155/2020/1073608.
Lotidis, M. A., P. P. Nomikos, and A. I. Sofianos. 2020. “Laboratory study of the fracturing process in marble and plaster hollow plates subjected to uniaxial compression by combined acoustic emission and digital image correlation techniques.” Rock Mech. Rock Eng. 53 (4): 1953–1971. https://doi.org/10.1007/s00603-019-02025-x.
Louis, L., T.-F. Wong, and P. Baud. 2007. “Imaging strain localization by X-ray radiography and digital image correlation: Deformation bands in Rothbach sandstone.” J. Struct. Geol. 29 (1): 129–140. https://doi.org/10.1016/j.jsg.2006.07.015.
Manouchehrian, A., and M. Cai. 2016. “Influence of material heterogeneity on failure intensity in unstable rock failure.” Comput. Geotech. 71: 237–246. https://doi.org/10.1016/j.compgeo.2015.10.004.
Munoz, H., A. Taheri, and E. K. Chanda. 2016. “Pre-peak and post-peak rock strain characteristics during uniaxial compression by 3D digital image correlation.” Rock Mech. Rock Eng. 49 (7): 2541–2554. https://doi.org/10.1007/s00603-016-0935-y.
Pan, P.-Z., X.-T. Feng, L.-F. Shen, S.-L. Qiu, and H. Zhou. 2011. “Effect of precrack length and inclination on tensile failure behaviour of heterogeneous rocks.” Mater. Res. Innovations 15 (sup1): s557–s560. https://doi.org/10.1179/143307511X12858957676678.
Pour, A. F., R. K. Verma, G. D. Nguyen, and H. H. Bui. 2022. “Analysis of transition from diffuse to localized failure in sandstone and concrete using digital image correlation.” Eng. Fract. Mech. 267: 108465. https://doi.org/10.1016/j.engfracmech.2022.108465.
Qi, Z. C., P. J. Ni, W. Jiang, X. G. Qiu, R. L. Wang, and W. G. Zhang. 2020. “Quantitative detection of minor defects in metal materials based on variation coefficient of CT image.” Optik 223: 165269. https://doi.org/10.1016/j.ijleo.2020.165269.
Ren, B., S. H. Wang, J. H. Xue, K. L. Qiu, G. F. Yu, Y. J. Fan, S. Q. Zhao, Z. Y. Du, D. S. Deng, and X. J. Hao. 2019. “Quantitative evaluation methods of brittle failure characteristics of coal: A case study of hard coal in China.” Geotech. Geol. Eng. 37 (3): 1421–1434. https://doi.org/10.1007/s10706-018-0696-3.
Shan, Z., J. Long, P. Yu, L. Shao, and Y. Liao. 2020. “Lightweight optimization of passenger car seat frame based on grey relational analysis and optimized coefficient of variation.” Struct. Multidiscip. Optim. 62 (6): 3429–3455. https://doi.org/10.1007/s00158-020-02647-8.
Shen, Y., and Z. Feng. 2022. “Study on precursor information of rock instability based on displacement increments measured at multiple points.” Nat. Hazard. 113: 1713–1727. https://doi.org/10.1007/s11069-022-05365-0.
Su, P., S. Tarkoma, and P. K. E. Pellikka. 2020. “Band ranking via extended coefficient of variation for hyperspectral band selection.” Remote Sens. 12 (20): 3319. https://doi.org/10.3390/rs12203319.
Thangjai, W., S. Niwitpong, and S. Niwitpong. 2020. “Confidence intervals for the common coefficient of variation of rainfall in Thailand.” PeerJ 8: e10004. https://doi.org/10.7717/peerj.10004.
Tudisco, E., S. A. Hall, E. M. Charalampidou, N. Kardjilov, A. Hilger, and H. Sone. 2015. “Full-field measurements of strain localisation in sandstone by neutron tomography and 3D-volumetric digital image correlation.” Physics Procedia 69: 509–515. https://doi.org/10.1016/j.phpro.2015.07.072.
Wang, J., J. Zhang, and C. Niu. 2014. “Study on key spring model of rock instability failure.” Hydrogeol. Eng. Geol. 41 (5): 38–43. https://doi.org/10.16030/j.cnki.issn.1000-3665.2014.05.034.
Wang, P., L. S. Jiang, X. Y. Li, P. Q. Zheng, and G. P. Qin. 2018. “Effects of strength weakening and interface slipping on rock mass with different dip angle structure planes.” Acta Geodyn. Geomater. 15 (4): 329–338. https://doi.org/10.13168/AGG.2018.0024.
Wang, Y., and F. Cui. 2018. “Energy evolution mechanism in process of sandstone failure and energy strength criterion.” J. Appl. Geophys. 154: 21–28. https://doi.org/10.1016/j.jappgeo.2018.04.025.
Xie, H. P., Y. Ju, L. Y. Li, and R. D. Peng. 2008. “Energy mechanism of deformation and failure of rock masses.” Chin. J. Rock Mech. Eng. 27 (9): 1729–1740.
Xie, M., W. Liu, Y. Du, Q. Li, and H. Wang. 2021a. “The evaluation method of rock mass stability based on natural frequency.” Adv. Civ. Eng. 2021: 1–9. https://doi.org/10.1155/2021/6652960.
Xie, S., H. Lin, Y. Chen, and Y. Wang. 2021b. “A new nonlinear empirical strength criterion for rocks under conventional triaxial compression.” J. Cent. South Univ. 28 (5): 1448–1458. https://doi.org/10.1007/s11771-021-4708-8.
Xu, J. K., R. Zhou, D. Z. Song, N. Li, K. Zhang, and D. Y. Xi. 2019. “Deformation and damage dynamic characteristics of coal–rock materials in deep coal mines.” Int. J. Damage Mech. 28 (1): 58–78. https://doi.org/10.1177/1056789517741950.
Xu, Q., Q. L. Yao, C. H. Shan, J. Q. Ma, and J. Li. 2022. “Comparative study on the deformation moduli of roadway surrounding rock in coal mines: A case study.” Bull. Eng. Geol. Environ. 81 (6): 220. https://doi.org/10.1007/s10064-022-02722-y.
Xu, X., and Q. C. Zhang. 2017. “High-accuracy, high-efficiency compensation method in two-dimensional digital image correlation.” Exp. Mech. 57 (6): 831–846. https://doi.org/10.1007/978-3-319-51439-0_15.
Xue, Y. G., X. M. Ma, D. H. Qiu, W. M. Yang, X. Li, F. M. Kong, B. H. Zhou, and C. Q. Qu. 2021. “Analysis of the factors influencing the nonuniform deformation and a deformation prediction model of soft rock tunnels by data miningTunnelling Underground Space Technol. 109: 103769. https://doi.org/10.1016/j.tust.2020.103769.
Yang, J., X. Liu, Z. Xu, H. Tang, and Q. Yu. 2020. “Full-field strain characterizations and fracture process of rock blasting using a small-scale double-hole bench model.” Adv. Civ. Eng. 2020: 1–13. https://doi.org/10.1155/2020/8649258.
Yang, S. Q., M. Chen, H. W. Jing, K. F. Chen, and B. Meng. 2017. “A case study on large deformation failure mechanism of deep soft rock roadway in Xin’An coal mine, China.” Eng. Geol. 217: 89–101. https://doi.org/10.1016/j.enggeo.2016.12.012.
You, W., F. Dai, Y. Liu, H. Du, and R. Jiang. 2021. “Investigation of the influence of intermediate principal stress on the dynamic responses of rocks subjected to true triaxial stress state.” Int. J. Min. Sci. Technol. 31 (5): 913–926. https://doi.org/10.1016/j.ijmst.2021.06.003.
Yu, H., and K. Ng. 2022. “Analytical model for failure strength of brittle rocks under triaxial compression and triaxial extension.” Int. J. Geomech. 22 (4): 06022003. https://doi.org/10.1061/(ASCE)GM.1943-5622.0002334.
Zahoor, M., and S. Puri. 2018. “Non-local continuum ductile damage model for rocks under high pressure and high temperature (HPHT).” J. Pet. Sci. Eng. 170: 655–663. https://doi.org/10.1016/j.petrol.2018.06.090.
Zhan, J., C. K. Wu, X. D. Ma, C. Q. Yang, Q. C. Miao, and S. L. Wang. 2022. “Abnormal vibration detection of wind turbine based on temporal convolution network and multivariate coefficient of variation.” Mech. Syst. Sig. Process. 174: 109082. https://doi.org/10.1016/j.ymssp.2022.109082.
Zhang, K., X. Liu, Y. Chen, and H. Cheng. 2021. “Quantitative description of infrared radiation characteristics of preflawed sandstone during fracturing process.” J. Rock Mech. Geotech. Eng. 13 (1): 131–142. https://doi.org/10.1016/j.jrmge.2020.05.003.
Zhang, L. G., G. Q. Qu, S. N. Qu, and Z. Y. Liu. 2018. “Constitutive model and elastic parameters for layered rock mass based on combined Hooke spring.” Strength Fract. Complexity 10 (3–4): 145–156. https://doi.org/10.3233/SFC-170206.
Zhang, Y., J. Wang, J. X. Zhao, G. Chen, P. Yu, and T. Yang. 2020a. “Multi-spring edge-to-edge contact model for discontinuous deformation analysis and its application to the tensile failure behavior of rock joints.” Rock Mech. Rock Eng. 53 (3): 1243–1257. https://doi.org/10.1007/s00603-019-01973-8.
Zhang, Y. B., J. M. Wang, J. X. Zhao, G. Q. Chen, P. C. Yu, and T. Yang. 2020b. “Multi-spring edge-to-edge contact model for discontinuous deformation analysis and its application to the tensile failure behavior of rock joints.” Rock Mech. Rock Eng. 53 (3): 1243–1257. https://doi.org/10.1007/s00603-019-01973-8.
Zhao, G. F., and K. W. Xia. 2018. “A study of mode-I self-similar dynamic crack propagation using a lattice spring model.” Comput. Geotech. 96: 215–225. https://doi.org/10.1016/j.compgeo.2017.11.001.
Zhao, T. B., W. Zhang, S. Gu, Y. Lv, and Z. Li. 2020. “Study on fracture mechanics of granite based on digital speckle correlation method.” Int. J. Solids Struct. 193–194: 192–199. https://doi.org/10.1016/j.ijsolstr.2020.02.026.
Zhao, Z. H., W. Sun, S. J. Chen, D. W. Yin, H. Liu, and B. S. Chen. 2021. “Determination of critical criterion of tensile-shear failure in Brazilian disc based on theoretical analysis and meso–macro numerical simulation.” Comput. Geotech. 134: 104096. https://doi.org/10.1016/j.compgeo.2021.104096.

Information & Authors

Information

Published In

Go to International Journal of Geomechanics
International Journal of Geomechanics
Volume 23Issue 9September 2023

History

Received: Jul 25, 2022
Accepted: Apr 3, 2023
Published online: Jul 5, 2023
Published in print: Sep 1, 2023
Discussion open until: Dec 5, 2023

Permissions

Request permissions for this article.

Authors

Affiliations

Xiangfeng Lv [email protected]
School of Civil and Resource Engineering, Univ. of Science and Technology Beijing, Beijing 100083, China; Beijing Key Laboratory of Urban Underground Space Engineering, Univ. of Science and Technology Beijing, Beijing 100083, China. Email: [email protected]
School of Civil and Resource Engineering, Univ. of Science and Technology Beijing, Beijing 100083, China (corresponding author). ORCID: https://orcid.org/0000-0003-1549-0666. Email: [email protected]
Nianjin Wang [email protected]
Power China Road Bridge Group Co., Ltd., Beijing 100032, China. Email: [email protected]
Power China Road Bridge Group Co., Ltd., Beijing 100032, China. Email: [email protected]
Zhongmeng Guo [email protected]
Power China Road Bridge Group Co., Ltd., Beijing 100032, China. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share