Advertisement

Time-varying characteristics on migration and loss of fine particles in fractured mudstone under water flow scour

  • Luzhen Wang
  • Hailing KongEmail author
  • Chengchun Qiu
  • Bing Xu
Original Paper
  • 47 Downloads

Abstract

It is very common in geotechnical engineering with Karst geological conditions that the fine particles migrate and lose continuously with water flow in the fractured rock mass, which will lead to the water-mud-inrush accident. In this paper, the time-varying characteristics of fine particles’ migration and loss in fractured mudstone under water flow scour were investigated experimentally and theoretically. Considering the continuous gradation of fractured mudstone, taking Talbot power exponent as the influencing factor, the time-varying features of the total lost mass were described. Based on the total lost mass, the mass-loss rate and the mass-migration rate of fine particles were proposed, and their time-varying features were compared and analyzed. The loss-migration-ratio was defined, and the water-mud-inrush risk was assessed by the relationships between loss-migration-ratio and time. The research showed that (1) the lost mass resulted from the fine particles’ migration, and the migrated mass was affected not only by lost fine particles but also by the water flow velocity. The rules of the fine particles’ migration and loss in the fractured mudstone had the non-linear and time-varying characteristics. (2) For samples with the smaller Talbot power exponent of n = 0.1–0.5, the fine particles splashing phenomenon occurred, and quite a lot of migrated fine particles were lost. The loss-migration-ratio attenuated with time by a power function. Fractured mudstone with this continuous gradation had a high water-mud-inrush risk. (3) For samples with n = 0.6–1.0, large numbers of fine particles migrated with water flow, but only a few rushed out from the fractured mudstone. The loss-migration-ratio attenuated with time by an exponent function. Fractured mudstone with this continuous gradation had a stable inner structure; therefore, the water-mud-inrush risk was very low. The results will help geotechnical practitioners to assess the water-mud-inrush risk and provide some references for the water-mud-inrush accidents prevention in geotechnical engineering with Karst geological conditions.

Keywords

Fractured mudstone Fine particles Migration and loss Talbot power exponent Mass-loss rate Mass-migration rate 

Abbreviations

a

The radius of the cylinder of the permeameter (L)

a1, a2, b1, b2

Coefficients (−)

d

The particle diameter of the current fractured mudstone (L)

D

The maximum particle diameter of fractured mudstone (L)

h

The loose height of the fractured mudstone in the cylinder (L)

mfp/mfpi

Mass of fine particles (M)

ml

Total lost mass (M)

mli

Total lost mass in the inrush mass loss stage (M)

mlf

Final total lost mass (M)

mlr

Total lost mass in the rapid mass loss stage (M)

M

Total mass of fractured mudstone (M)

Md

Mass of fractured mudstone with particles diameters no greater than d (M)

n

Talbot power exponent (−)

P(d)

Percentage of the mass of the particle whose diameter is less than d (−)

Pif

The percentage that mli accounts for mlf (−)

Prf

The percentage that mlraccounts for mlf(−)

ql/qli

Mass-loss rate (MT−1 L−3)

qlmax

The maximum value of the mass-loss rate (MT−1 L−3)

qm/qmi

Mass-migration rate (MT−1 L−3)

qmmax

The maximum value of the mass-migration rate (MT−1 L−3)

qs/qsi

Water flow scour rate (MT−1 L−3)

t

Water flow time (T)

uw

Water flow velocity (LT−1)

ufp

Fine particles’ migration velocity (LT−1)

V

Normal volume of the fractured mudstone at the loose state in the cylinder (L3)

ρfp/ρfpi

Mass concentration of the fine particles in the pore of fractured mudstone (ML−3)

Δmi

Mass of lost fine particles in the collection time Δti (M)

Δti

Collection time of the lost fine particles (T)

η

Loss-migration-ratio (−)

Notes

Funding information

This work was supported by the National Natural Science Fund (11502229, 51808481), the Natural Science Foundation of Jiangsu Province of China (BK20160433), the Outstanding Young Backbone Teacher of QingLan Project in Jiangsu Province (2016), the Program of Outstanding Young Scholars in Yancheng Institute of Technology (2014), the Program of Yellow Sea Elite in Yancheng Institute of Technology (2019) and College Students’ Innovation and Entrepreneurship Training Program (2018).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Chu V (2016) Mechanism on water inrush disaster of filling karst piping and numerical analysis of evolutionary process in highway tunnel. J Central South Univ (Sci Technol) 47(12):4173–4180Google Scholar
  2. Chu HD, Xu GL, Yasufuku N, Yu Z, Liu PL, Wang JF (2017) Risk assessment of water inrush in karst tunnels based on two-class fuzzy comprehensive evaluation method. Arab J Geosci 10(7):1–12CrossRefGoogle Scholar
  3. Hao YQ, Rong XL, Lu H, Xiong ZM, Dong X (2018) Quantification of margins and uncertainties for the risk of water inrush in a karst tunnel: representations of epistemic uncertainty with probability. Arab J Sci Eng 43(4):1627–1640CrossRefGoogle Scholar
  4. Herman EK, Toran L, White WB (2009) Quantifying the place of karst aquifers in the groundwater to surface water continuum: A time series analysis study of storm behavior in Pennsylvania water resources. J Hydrol 376(1):307–317CrossRefGoogle Scholar
  5. Hu H, Zhang BW, Zuo YY, Zhang CM, Wang YZ, Guo Z (2018) The mechanism and numerical simulation analysis of water bursting in filling karst tunnel. Geotech Geol Eng 36:1197–1205CrossRefGoogle Scholar
  6. Hubei Hu-Rong-Xi Expressway Construction Headquarters (2009) The research of geological disaster control in high risk karst tunnel. Hubei Hu-Rong-Xi Expressway Construction Headquarters, WuhanGoogle Scholar
  7. Kong HL, Wang LZ (2018a) The mass loss behavior of fractured rock in seepage process: the development and application of a new seepage experimental system. Ad Civ Eng 7891914:1–12Google Scholar
  8. Kong HL, Wang LZ (2018b) Seepage problems on fractured rock accompanying with mass loss during excavation in coal mines with karst collapse columns. Arab J Geosci 11(19):1–13CrossRefGoogle Scholar
  9. Li TZ, Yang XL (2018) Risk assessment model for water and mud inrush in deep and long tunnels based on normal grey cloud clustering method. KSCE J Civ Eng 22(5):1991–2001CrossRefGoogle Scholar
  10. Li LP, Li SC, Chen J, Li JH, Xu ZH, Shi SS (2011) Construction license mechanism and its application based on karst water inrush risk evaluation. Chin J Rock Mech Eng 30(7):1345–1355Google Scholar
  11. Li SC, Zhou ZQ, Li LP, Shi SS, Xu ZH (2013) Risk evaluation theory and method of water inrush in karst tunnels and its applications. Chin J Rock Mech Eng 32(9):1858–1867Google Scholar
  12. Li LP, Lei T, Li SC, Xu ZH, Shi SS (2015a) Dynamic risk assessment of water inrush in tunnelling and software development. Geomech Eng 9(1):57–81CrossRefGoogle Scholar
  13. Li LP, Lei T, Li SC, Zhang QQ, Xu ZH, Shi SS, Zhou ZQ (2015b) Risk assessment of water inrush in karst tunnels and software development. Arab J Geosci 8(4):1843–1854CrossRefGoogle Scholar
  14. Li TC, Lyu LX, Duan HL, Chen W (2016) Water burst mechanism of deep buried tunnel passing through weak water-rich zone. J Central South Univ (Sci Technol) 47(10):3469–3476Google Scholar
  15. Li LP, Chen DY, Li SC, Shi SS, Zhang MG, Liu HL (2017a) Numerical analysis and fluid-solid coupling model test of filling-type fracture water inrush and mud gush. Geomech Eng 13(6):1011–1025Google Scholar
  16. Li SC, Wu J, Xu ZH, Li LP (2017b) Unascertained measure model of water and mud inrush risk evaluation in karst tunnels and its engineering application. KSCE J Civ Eng 21(4):1170–1182CrossRefGoogle Scholar
  17. Li SC, Wu J, Xu ZH (2018) Escape route analysis after water inrush from the working face during submarine tunnel excavation construction. Mar Georesour Geotechnol 37(4):379–392CrossRefGoogle Scholar
  18. Liang DX, Jiang ZQ, Zhu SY, Sun Q, Qian ZW (2016) Experimental research on water inrush in tunnel. Nat Hazards 81(1):467–480CrossRefGoogle Scholar
  19. Liu JQ, Chen WZ, Yang DS, Yuan JQ, Li XF, Zhang QY (2017a) Nonlinear seepage-erosion coupled water inrush model for completely weathered granite. Mar Georesour Geotechnol 36(4):484–493CrossRefGoogle Scholar
  20. Liu JQ, Yang DS, Chen WZ, Yuan JQ, Li CJ, Qi XY (2017b) Research on particle starting velocity in the expansion of water inrush channel in completely weathered granite. Rock Soil Mech 38(4):1179–1187Google Scholar
  21. Liu JQ, Chen WZ, Liu TG, Yu JX, Dong JL, Nie W (2018) Effects of initial porosity and water pressure on seepage-erosion properties of water inrush in completely weathered granite. Geofluids 4103645:1–11Google Scholar
  22. Pan DD, Li SC, Xu ZH, Li LP, Lu W, Lin P (2018) Model tests and numerical analysis for water inrush caused by karst caves filled with confined water in tunnels. Chin J Geotec Eng 40(5):828–836Google Scholar
  23. Peng YX, Wu L, Su Y, Zhou RF (2016) Risk prediction of tunnel water or mud inrush based on disaster forewarning grading. Geotech Geol Eng 34(6):1923–1932CrossRefGoogle Scholar
  24. Qian QH (2012) Challenges faced by underground projects construction safety and countermeasures. Chin J Rock Mech Eng 31(10):1945–1956Google Scholar
  25. Shi SS, Xie XK, Bu L, Li LP, Zhou ZQ (2018) Hazard-based evaluation model of water inrush disaster sources in karst tunnels and its engineering application. Environ Earth Sci 77(4):1–13CrossRefGoogle Scholar
  26. Wang LZ, Kong HL (2017) Accelerated experimental study on permeability for broken rock accompanying with mass loss. The Science Publishing Company, BeijingGoogle Scholar
  27. Wang LZ, Kong HL (2018) Variation characteristics of mass-loss rate in dynamic seepage system of the broken rocks. Geofluids 7137601:1–17Google Scholar
  28. Wang DM, Zhang QS, Zhang X, Wang K, Tan YH (2016a) Model experiment on inrush of water and mud and catastrophic evolution in a fault fracture zone tunnel. Rock Soil Mech 37(10):2851–2860Google Scholar
  29. Wang K, Li SC, Zhang QS, Zhang X, Li LP, Zhang QQ, Liu C (2016b) Development and application of new similar materials of surrounding rock for a fluid-solid coupling model test. Rock Soil Mech 37(9):2521–2533Google Scholar
  30. Wang YC, Yin X, Jing HW, Liu RC, Su HJ (2016c) A novel cloud model for risk analysis of water inrush in karst tunnels. Environ Earth Sci 75(22):1–13Google Scholar
  31. Wang LZ, Chen ZQ, Kong HL (2017a) An experimental investigation for seepage-induced instability of confined broken mudstones with consideration of mass loss. Geofluids 3057910:1–12Google Scholar
  32. Wang YC, Yin X, Geng F, Jing HW, Su HJ, Liu RC (2017b) Risk assessment of water inrush in karst tunnels based on the efficacy coefficient method. Polish J Environ Stud 26(4):1765–1775CrossRefGoogle Scholar
  33. Wu J, Li SC, Xu ZH (2017) Flow characteristics and escape-route optimization after water inrush in a backward-excavated karst tunnel. Int J Geomech 17(4):1–16CrossRefGoogle Scholar
  34. Wu J, Li SC, Xu ZH, Pan DD (2018) Flow characteristics after water inrush from the working face in karst tunneling. Geomech Eng 14(5):407–419Google Scholar
  35. Yang XL, Zhang SS (2018) Risk assessment model of tunnel water inrush based on improved attribute mathematical theory. J Central South Univ 25(2):379–391CrossRefGoogle Scholar
  36. Yang WM, Wang H, Yang X, Zhang B, Yang L, Fang ZD, Wang MX (2017) Development and application of model test system for water inrush in high-geostress and high hydraulic pressure tunnels. Chin J Rock Mech Eng 36(S2):3992–4001Google Scholar
  37. Yuan YC, Li SC, Zhang QQ, Li LP, Shi SS, Zhou ZQ (2016) Risk assessment of water inrush in karst tunnels based on a modified grey evaluation model: sample as Shangjiawan Tunnel. Geomech Eng 11(4):493–513CrossRefGoogle Scholar
  38. Zhang QS, Wang DM, Li SC, Zhang X, Tan YH, Wang K (2017) Development and application of model test system for inrush of water and mud of tunnel in fault rupture zone. Chin J Geotech Eng 39(3):417–426Google Scholar
  39. Zhao YL, Zhang LY (2018) Experimental study on the mud-water inrush characteristics through rock fractures. Ad Civ Eng 2060974:1–7Google Scholar
  40. Zhou ZQ, Li SC, Li LP, Shi SS, Xu ZH (2015a) An optimal classification method for risk assessment of water inrush in karst tunnels based on grey system theory. Geomech Eng 8(5):631–647CrossRefGoogle Scholar
  41. Zhou Y, Li SC, Li LP, Shi SS, Zhang QQ, Chen DY, Song SG (2015b) 3D fluid-solid coupled model test on water-inrush in tunnel due to seepage from filled karst conduit. Chin J Rock Mech Eng 34(9):1739–1749Google Scholar
  42. Zhu BB, Wu L, Peng YX, Zhou WW, Chen CH (2018) Risk assessment of water inrush in tunnel through water-rich fault. Geotech Geol Eng 36(1):317–326CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  1. 1.College of Civil EngineeringYancheng Institute of TechnologyYanchengChina

Personalised recommendations