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Mechanical evolution of constant resistance and large deformation anchor cables and their application in landslide monitoring

  • Zhigang Tao
  • Yong Wang
  • Chun ZhuEmail author
  • Huixia Xu
  • Gan Li
  • Manchao He
Original Paper
  • 35 Downloads

Abstract

Landslides are a common disaster in open-pit mining and are difficult to effectively monitor and provide early warnings for with conventional methods. A remote monitoring and forecasting system for landslides is developed using constant resistance and large deformation (CRLD) anchor cable to control impact resistance, large deformation, and energy absorption. Slow tension and instantaneous impact are generated on the CRLD anchor cable during development and penetration of the sliding surface. Both the static tensile test and dynamic impact test verify that the CRLD anchor cables maintain a high constant resistance, large deformation, and high energy absorption under the action of impact force and static force. Under static tension and dynamic impact, the CRLD anchor cable has advantages of large deformation, high constant resistance, stable performance, and advanced critical landslide warning. By applying CRLD anchor cables to the monitoring of Nanfen open-pit slopes in China, the 2016-11-01 landslide was successfully forecasted 4 h prior to the event, guaranteeing mine safety and providing the theoretical and practical basis for an advanced monitoring and early warning for landslides.

Keywords

CRLD anchor cable Static tensile test Dynamic impact test Energy absorption Landslide monitoring and early warning 

Notes

Acknowledgements

This work was supported by the Key Research and Development Project of Zhejiang Province (Grant No:2019C03104 ) and National Natural Science Foundation of China (No. 51508092).

References

  1. Chen Y, Uchimura T, Irfan M et al (2017) Detection of water infiltration and deformation of unsaturated soils by elastic wave velocity. Landslides 14(3):1–16.  https://doi.org/10.1007/s10346-017-0825-8 Google Scholar
  2. Chen Y, Irfan M, Uchimura T, Cheng G, Nie W (2018) Elastic wave velocity monitoring as an emerging technique for rainfall-induced landslide prediction. Landslides 15(6):1155–1172.  https://doi.org/10.1007/s10346-017-0943-3 CrossRefGoogle Scholar
  3. Eker R, Aydın A (2014) Assessment of forest road conditions in terms of landslide susceptibility: a case study in Yığılca Forest Directorate (Turkey). Turk J Agric For 38:281–290.  https://doi.org/10.3906/tar-1303-12 CrossRefGoogle Scholar
  4. Fernández T, Pérez JL, Cardenal FJ et al (2016) Analysis of landslide evolution affecting olive groves using UAV and photogrammetric techniques. Remote Sens 8(10):83.  https://doi.org/10.3390/rs8100837 CrossRefGoogle Scholar
  5. He MC (2009) Real-time remote monitoring and forecasting system for geological disasters of landslides and its engineering application. China J Rock Mech Eng, 2009 28(6):1081–1090.  https://doi.org/10.3321/j.issn:1000-6915.2009.06.001 Google Scholar
  6. He MC, Gong WL, Wang J et al (2014) Development of a novel energy-absorbing bolt with extraordinarily large elongation and constant resistance. Int J Rock Mech Mining Sci 67(67):29–42.  https://doi.org/10.1016/j.ijrmms.2014.01.007 CrossRefGoogle Scholar
  7. Huang WP, Li C, Zhang LW et al (2018) In situ identification of water-permeable fractured zone in overlying composite strata. Int J Rock Mech Min Sci 105:85–97.  https://doi.org/10.1016/j.ijrmms.2018.03.013 CrossRefGoogle Scholar
  8. Jaboyedoff M, Oppikofer T, Abellán A et al (2012) Use of LIDAR in landslide investigations: a review. Nat Hazards 61(1):5–28.  https://doi.org/10.1007/s11069-010-9634-2 CrossRefGoogle Scholar
  9. Li Y, Zhang S, Zhang X (2018) Classification and fractal characteristics of coal rock fragments under uniaxial cyclic loading conditions. Arab J Geosci 11(9):201.  https://doi.org/10.1007/s12517-018-3534-2 CrossRefGoogle Scholar
  10. Lindner G, Schraml K, Mansberger R, Hübl J (2016) UAV monitoring and documentation of a large landslide. Appl Geomatics 8(1):1–11.  https://doi.org/10.1007/s12518-015-0165-0 CrossRefGoogle Scholar
  11. Niethammer U, James MR, Rothmund S, Travelletti J, Joswig M (2012) UAV-based remote sensing of the super-Sauze landslide: evaluation and results. Eng Geol 128:2–11.  https://doi.org/10.1016/j.enggeo.2011.03.012 CrossRefGoogle Scholar
  12. Ohbayashi R, Nakajima Y, Nishikado H, et al (2008) Monitoring system for landslide disaster by wireless sensing node network[C]//Proceedings of SICE Annual Conference. [S.l.]: [s.n.]: 1704-1710Google Scholar
  13. Peternel T, Kumelj S, Ostir K, Komac M (2017) Monitoring the Potoška planina landslide (NW Slovenia) using UAV photogrammetry and tachymetric measurements. Landslides 14(1):395–406.  https://doi.org/10.1007/s10346-016-0759-6 CrossRefGoogle Scholar
  14. Puglisi G, Bonaccorso A, Mattia M (2005) New integrated geodetic monitoring system at Stromboli volcano (Italy). Eng Geol 79(1):13–31.  https://doi.org/10.1016/j.enggeo.2004.10.013 CrossRefGoogle Scholar
  15. Reevea B A, Stickley G F, Noon D A, et al (2000) Developments in monitoring mine slope stability using radar interferometry[C]//Proceedings of IEEE 2000 International Geoscience and Remote Sensing Symposium. [S.l.]: [s.n.]: 2325–2327.  https://doi.org/10.1109/IGARSS.2000.858397
  16. Rose ND, Hungr O (2007) Forecasting potential rock slope failure in open-pit mines using the inverse-velocity method. Int J Rock Mech Min Sci 44(2):308–320.  https://doi.org/10.1016/j.ijrmms.2006.07.014 CrossRefGoogle Scholar
  17. Scaioni M (2015) Modern technologies for landslide monitoring and prediction. Springer Natural Hazards, 2015, 249.  https://doi.org/10.1007/978-3-662-45931-7
  18. Stumpf A (2013) Landslide recognition and monitoring with remotely sensed data from passive optical sensors. PhD Thesis, University of StrasbourgGoogle Scholar
  19. Tang H, Li C, Hu X et al (2015) Evolution characteristics of the Huangtupo landslide based on in situ tunneling and monitoring. Landslides 12(3):511–521.  https://doi.org/10.1007/s10346-014-0500-2 CrossRefGoogle Scholar
  20. Tao ZG, Pang SH, Zhou Y et al (2017) Static pull testing of a new type of large deformation cable with constant resistance. Adv Mater Sci Eng:1:1–1:9.  https://doi.org/10.1155/2017/5198049
  21. Tao ZG, Li M, Zhu C et al (2018a) Analysis of the critical safety thickness for pretreatment of mined-out areas underlying the final slopes of open-pit mines and the effects of treatment. Shock Vib 2018:1–14.  https://doi.org/10.1155/2018/1306535 Google Scholar
  22. Tao ZG, Zhu C, Zheng X, et al (2018b) Slope stability evaluation and monitoring of Tonglushan ancient copper mine relics, 10(8): 1-16.  https://doi.org/10.1177/1687814018791707
  23. Tsai ZX, You GJY, Lee HY, Chiu YJ (2012) Use of a total station to monitor post-failure sediment yields in landslide sites of the Shihmen Reservoir watershed, Taiwan. Geomorphology 139-140:438–451.  https://doi.org/10.1016/j.geomorph.2011.11.008 CrossRefGoogle Scholar
  24. Wang Z, Sun H, Shang Y (2011) Time series analysis of landslide prediction based on groundwater level variation. Chin J Rock Mech Eng 30(11):2276–2284.  https://doi.org/10.1371/journal.pgen.1004818 Google Scholar
  25. Wang X, Wen Z, Jiang Y et al (2018) Experimental study on mechanical and acoustic emission characteristics of rock-like material under non-uniformly distributed loads. Rock Mech Rock Eng 51(3):729–745.  https://doi.org/10.1007/s00603-017-1363-3 CrossRefGoogle Scholar
  26. Warrick JA, Ritchie AC, Adelman G et al (2017) New techniques to measure cliff change from historical oblique aerial photographs and structure-from-motion photogrammetry. J Coast Res 33(1):39–55.  https://doi.org/10.2112/JCOASTRES-D-16-00095.1 CrossRefGoogle Scholar
  27. Wyllie D, Mah C (2004) Rock Slope Engineering, Civil and mining, 4th edition [M]. Spon Press, Taylor & Francis GroupGoogle Scholar
  28. Zhu C, Tao ZG, Yang S, Zhao S (2018) V-shaped gully method for controlling rockfall on high-steep slopes in China. Bull Eng Geol Environ 2018(2018):1–17.  https://doi.org/10.1007/s10064-018-1269-7 Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.State Key Laboratory for Geomechanics & Deep Underground EngineeringBeijingChina
  2. 2.School of Mechanics and Civil EngineeringChina University of Mining & Technology (Beijing)BeijingChina
  3. 3.College of Construction EngineeringJilin UniversityChangchunChina

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