Investigation on inspection scheduling for the maintenance of tunnel with different degradation modes

Abstract Inspection scheduling is an important task in the maintenance of tunnels, which will obviously affect the lifetime maintenance cost and risk. Traditional periodic inspection with fixed inspection interval has low efficiency in the early age or high risk in the later age of tunnel. This study aims at developing a novel non-periodic inspection policy and investigating the adaptability of several inspection scheduling functions with different degradation modes. Three classical degradation modes (namely, accelerated, decelerated and stationary) are categorized to describe the potential trends of degradation, and they are modeled by non-stationary Gamma process in a unified form. The effects of three types of inspection scheduling functions on the tunnel maintenance are compared in the view of the expectation of lifetime maintenance cost. The results of the numerical analysis show that inspection schedule function f 2 ( x ) (in the form of a convex curve) always yields the lowest maintenance cost, regardless of the degradation mode of tunnel. The results indicate that the inspection scheduling function in the type of a convex function is the best and shortening the inspection interval is an effective measure to reduce maintenance cost and risk. The proposed method and the obtained results are helpful for practitioners to make more effective inspection scheduling and to reduce both risk and cost associated with the maintenance of tunnels.

[1]  Mohamed Marzouk,et al.  Multiobjective optimisation algorithm for sewer network rehabilitation , 2013 .

[2]  Khalid M. Mosalam,et al.  Development and application of the integrated sealant test apparatus for sealing gaskets in tunnel segmental joints , 2017 .

[3]  WooSeok Kim,et al.  Bridge inspection practices and bridge management programs in China, Japan, Korea, and U.S. , 2018 .

[4]  Khalid M. Mosalam,et al.  Performance-based design of joint waterproofing of segmental tunnel linings using hybrid computational/experimental procedures , 2020 .

[5]  Yong Yuan,et al.  Rapid Acquisition and Identification of Structural Defects of Metro Tunnel , 2019, Sensors.

[6]  Dan M. Frangopol,et al.  Gamma prediction models for long-term creep deformations of prestressed concrete bridges , 2017 .

[7]  Wei Yang,et al.  Time-dependent reliability method for service life prediction of reinforced concrete shield metro tunnels , 2018 .

[8]  Dongming Zhang,et al.  Deformational responses of operated shield tunnel to extreme surcharge: a case study , 2017 .

[9]  Rommert Dekker,et al.  Modelling and Optimizing Imperfect Maintenance of Coatings on Steel Structures , 2007 .

[10]  Zihan Zhang,et al.  Dynamic maintenance strategy with iteratively updated group information , 2020, Reliab. Eng. Syst. Saf..

[11]  Sankaran Mahadevan,et al.  Maintenance strategies optimisation of metro tunnels in soft soil , 2017 .

[12]  Hongwei Huang,et al.  Resilience analysis of shield tunnel lining under extreme surcharge: Characterization and field application , 2016 .

[13]  Yong Yuan,et al.  State-oriented maintenance strategy for deteriorating segmental lining of tunnel , 2018 .

[14]  Rommert Dekker,et al.  A comparison of models for measurable deterioration: An application to coatings on steel structures , 2006, Reliab. Eng. Syst. Saf..

[15]  Michael N. Grussing Optimized Building Component Assessment Planning Using a Value of Information Model , 2018 .

[16]  Antoine Grall,et al.  A condition-based maintenance policy with non-periodic inspections for a two-unit series system , 2005, Reliab. Eng. Syst. Saf..

[17]  C Li,et al.  Risk-cost optimised maintenance strategy for tunnel structures , 2017 .

[18]  Hao Peng,et al.  A condition-based maintenance policy for multi-component systems with a high maintenance setup cost , 2015, OR Spectr..

[19]  Haotian Liu,et al.  Adaptive optimisation methods in system-level bridge management , 2015 .

[20]  Xian Liu,et al.  Experimental investigation of the ultimate bearing capacity of continuously jointed segmental tunnel linings , 2016 .

[21]  José C. Matos,et al.  Comparison of stochastic prediction models based on visual inspections of bridge decks , 2017 .

[22]  Bilal M. Ayyub,et al.  Field data-based probabilistic assessment on degradation of deformational performance for shield tunnel in soft clay , 2017 .

[23]  Yongxu Xia,et al.  Complex Variable Solutions for Forces and Displacements of Circular Lined Tunnels , 2018, Mathematical Problems in Engineering.

[24]  Antoine Grall,et al.  A condition-based maintenance policy for stochastically deteriorating systems , 2002, Reliab. Eng. Syst. Saf..

[25]  Liu Sheng-li Study on the Fatigue Life of the Tunnel Bed Structure under Train Loads , 2007 .

[26]  Lirong Cui,et al.  Maintenance policies for energy systems subject to complex failure processes and power purchasing agreement , 2018, Comput. Ind. Eng..

[27]  Christophe Bérenguer,et al.  Condition‐Based Maintenance with Imperfect Preventive Repairs for a Deteriorating Production System , 2012, Qual. Reliab. Eng. Int..

[28]  Tarek Zayed,et al.  Fitness-oriented multi-objective optimisation for infrastructures rehabilitations , 2015 .

[29]  Kenichi Soga,et al.  Comparison of the structural behavior of reinforced concrete and steel fiber reinforced concrete tunnel segmental joints , 2017 .

[30]  Jianhong Wang,et al.  Framework for maintenance management of shield tunnel using structural performance and life cycle cost as indicators , 2017, Life-Cycle of Structural Systems.

[31]  Kenichi Soga,et al.  Rehabilitation of Overdeformed Metro Tunnel in Shanghai by Multiple Repair Measures , 2019, Journal of Geotechnical and Geoenvironmental Engineering.

[32]  Yin-Fu Jin,et al.  Optimization techniques for identifying soil parameters in geotechnical engineering: Comparative study and enhancement , 2018 .

[33]  C. T. Barker,et al.  Optimal non-periodic inspection for a multivariate degradation model , 2009, Reliab. Eng. Syst. Saf..

[34]  Yong Yuan,et al.  Probabilistic Assessment for Concrete Spalling in Tunnel Structures , 2017 .

[35]  Jianhang Liu,et al.  Assessment service state of tunnel structure , 2012 .

[36]  A. Firouzi,et al.  Time dependent reliability analysis of railway sleepers subjected to corrosion , 2018, Structural Concrete.

[37]  Yongxu Xia,et al.  Analytic Solutions of the Forces and Displacements for Multicentre Circular Arc Tunnels , 2018 .

[38]  Yong Yuan,et al.  Acquiring sectional profile of metro tunnels using charge-coupled device cameras , 2016 .

[39]  Jan M. van Noortwijk,et al.  A survey of the application of gamma processes in maintenance , 2009, Reliab. Eng. Syst. Saf..

[40]  J. Holmén Fatigue of Concrete by Constant and Variable Amplitude loading , 1982 .

[41]  Shui-Long Shen,et al.  Selection of sand models and identification of parameters using an enhanced genetic algorithm , 2016 .

[42]  Kenichi Soga,et al.  Failure mechanism of joint waterproofing in precast segmental tunnel linings , 2019, Tunnelling and Underground Space Technology.

[43]  J. de Brito,et al.  Statistical modelling of carbonation in reinforced concrete , 2014 .

[44]  Shui-Long Shen,et al.  Risk Assessment Using a New Consulting Process in Fuzzy AHP , 2020 .

[45]  K. Tuutti Corrosion of steel in concrete , 1982 .

[46]  Xiaomo Jiang,et al.  Probabilistic degradation modelling of circular tunnels assembled from segmental linings , 2016 .

[47]  Lirong Cui,et al.  Optimal maintenance policy considering maintenance errors for systems operating under performance-based contracts , 2017, Comput. Ind. Eng..

[48]  Leonardo P. Santiago,et al.  A condition-based maintenance policy and input parameters estimation for deteriorating systems under periodic inspection , 2011, Comput. Ind. Eng..

[49]  Yu Zhao,et al.  Opportunistic maintenance of production systems subject to random wait time and multiple control limits , 2018 .

[50]  X. Gu,et al.  Modeling time-dependent circumferential non-uniform corrosion of steel bars in concrete considering corrosion-induced cracking effects , 2019 .