Tunnel lining crack expansion and maintenance strategy optimization considering train loads: A case study

Author:

Wang DapengORCID,Wang Jingchun,Rao Chengjie,Niu Xing,Xu Qiang

Abstract

Cracks in concrete tunnel linings are inevitable during service life. It is necessary to keep abreast of the cracking condition of the lining and formulate reasonable inspection and maintenance measures to ensure operational safety. Considering the influence of train loads on the safety and service performance of cracked linings, the expansion process of lining cracks and the maintenance strategy of tunnels during the service period was investigated. The impact of detection probability and maintenance measures on the service life of tunnel lining and the cost of detection and maintenance of cracked lining in the whole life cycle was analyzed; the optimization calculation model of tunnel lining crack detection and maintenance strategy based on genetic algorithm was established with the multi-objective optimization function of maximizing the service life of detection and maintenance and minimizing the total cost of detection and maintenance of fatigue cracks. The optimization analysis of lining crack expansion, detection, and maintenance was carried out for an operational railroad tunnel. Finally, an optimization analysis of lining crack expansion and maintenance was carried out in a railway tunnel. The results show that the stress intensity factor at the tip of the lining cracks is the same as the train load waveform; the magnitude of the stress intensity factor approximately satisfies the exponential function relationship with the depth of cracks; the fatigue service life of cracked lining is positively correlated with the cost of inspection and maintenance; the adoption of the necessary maintenance and the increase in the number of inspections and maintenance have a better economy while meeting the expectation of the service life. According to the Pareto solution set, the management can formulate the inspection and maintenance strategy based on the tunnel’s expected life and maintenance budget.

Funder

National Natural Science Foundation of China

Graduate student innovation ability training funding Project of Hebei Provincial Department of Education

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

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