Safety Evaluation of Plain Concrete Lining Considering Deterioration and Aerodynamic Effects

Abstract

With an increase in the service time of high-speed railway tunnels, various defects caused by construction-quality defects in the secondary lining begin to appear. How to evaluate the safety of such tunnels and take countermeasures is very important for the safe operation of tunnels. Based on the load-structure method and a numerical simulation, this paper studied the short-term and long-term safety of the missing section of anti-crack reinforcement mesh in the plain concrete lining of a high-speed railway mountain tunnel. The short-term safety evaluation considered the influence of negative pressure caused by aerodynamic effects. The long-term safety evaluation considered the combined influence of the surrounding rock and concrete deterioration and the negative pressure and concrete fatigue damage caused by aerodynamic effects. The results showed that under the negative pressure generated by aerodynamic effects, the minimum tensile safety factor of the lining in the defective section increased by 3.8%, while the minimum compressive safety factor of the lining decreased by 7.9%. The negative pressure generated by the aerodynamic effects had little impact on the short-term safety of the lining in the defective section. During the long-term safety evaluation, the overall safety of the defective section decreased significantly, and the minimum tensile and minimum compressive safety factors of the lining decreased by 59.4% and 66.8%, respectively. The calculation results for the initial design do not meet the long-term design requirements and cannot guarantee the long-term safe operation of the tunnel. Finally, two new strengthening methods of galvanized steel mesh-short bolts and galvanized corrugated steel plate-short bolts were proposed to strengthen the defective section of the concrete lining, so as to improve the ultimate bearing capacity and toughness of the plain concrete lining structure.

Using Ground-Penetrating Radar and Deep Learning to Rapidly Detect Voids and Rebar Defects in Linings

“…These issues seriously impact the normal use and operational safety of tunnels [1]. Thus, effectively understanding the classification, location, and shape of lining internal defects is crucial in providing the necessary foundations for timely problem solving and ensuring the safety of tunnels [2].…”