Stability Analysis of Karst Tunnels Based on a Strain Hardening–Softening Model and Seepage Characteristics

Hongyang Liu, Zhibin Lin, Chengwei Liu, Boyang Zhang, Chen Wang, Jiangang Liu and Huajie Liang
Additional contact information
Hongyang Liu: School of Mining and Mechanical Engineering, Liupanshui Normal University, Liupanshui 553004, China
Zhibin Lin: School of Civil Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Chengwei Liu: School of Mining and Mechanical Engineering, Liupanshui Normal University, Liupanshui 553004, China
Boyang Zhang: School of Civil Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Chen Wang: School of Mining, Guizhou University, Guiyang 550025, China
Jiangang Liu: School of Mining and Mechanical Engineering, Liupanshui Normal University, Liupanshui 553004, China
Huajie Liang: School of Mining and Mechanical Engineering, Liupanshui Normal University, Liupanshui 553004, China

Sustainability, 2022, vol. 14, issue 15, 1-19

Abstract: There are more and more tunnel projects in the karst-developed areas in Southwest China. Affected by karst caves and water, karst tunnels often experience geological disasters such as local collapses and water inrush. A simplified rock stress hardening-softening model was established based on the triaxial compression test results of two kinds of carbonatite to accurately analyze the deformation and water inrush characteristics of the surrounding rocks after karst tunnel excavation. The total stress–strain curve of rocks was simplified into four linear stages: the linear elastic stage, strain hardening stage, strain-softening stage, and residual stage. The volumetric strain–axial strain curve was simplified into four corresponding linear stages: the elastic expansion stage, slow expansion stage, rapid expansion stage, and stable expansion stage. The stress hardening–softening model was used to deduce the relationship between the rocks’ mechanical parameters such as cohesion, internal friction angle, dilatancy angle, and plastic strain, as well as the relationship between seepage characteristic parameters such as permeability coefficient, porosity, and volumetric strain. A karst tunnel in Chongqing, China was taken as the engineering background. The stress hardening–softening constitutive model and seepage characteristic parameters were applied to the FLAC 3D numerical simulation by the programming language FISH to analyze the stability and water inrush characteristics of karst tunnels in overlying confining caves. The results showed that rock masses between the cave and tunnel were prone to overall sliding instability. Confined water in the karst cave intruded into the tunnel through the shear-slip rupture zone on both sides instead of the shortest path. Two water inrush points existed on the tunnel surface. The variation law of the permeability coefficients of the surrounding rocks could more truly reflect whether there was a seepage channel between the tunnel and karst cave, as well as the permeable area and water inrush speed of the seepage channel. The work provides a new idea for the stability control of karst tunnels.

Keywords: strain hardening-softening model; mechanical parameters; seepage characteristics; karst tunnel; programming language FISH (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/15/9589/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/15/9589/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:15:p:9589-:d:880308

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().