Browse > Article
http://dx.doi.org/10.12989/cac.2013.12.1.091

Reliability assessment of concrete bridges subject to corrosion-induced cracks during life cycle using artificial neural networks  

Firouzi, Afshin (Construction Engineering and Management Group, Islamic Azad University, Science and Research Branch)
Rahai, Alireza (Department of Civil Engineering, Amirkabir University of Technology)
Publication Information
Computers and Concrete / v.12, no.1, 2013 , pp. 91-107 More about this Journal
Abstract
Corrosion of RC bridge decks eventually leads to delamination, severe cracking and spalling of the concrete cover. This is a prevalent deterioration mechanism and demands for the most costly repair interventions during the service life of bridges worldwide. On the other hand, decisions for repairs are usually made whenever the extent of a limit crack width, reported in routine visual inspections, exceeds an acceptable threshold level. In this paper, while random fields are applied to account for spatial variation of governing parameters of the corrosion process, an analytical model is used to simulate the corrosion induced crack width. However when dealing with random fields, the Monte Carlo simulation is apparently an inefficient and time consuming method, hence the utility of neural networks as a surrogate in simulation is investigated and found very promising. The proposed method can be regarded as an invaluable tool in decision making concerning maintenance of bridges.
Keywords
concrete; corrosion; random field; ANN; Monte carlo;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Duprat, F. (2007), "Reliability of RC beams under chloride ingress", Constr. Build. Mater., 21, 1605-1616.   DOI   ScienceOn
2 Duracrete (2000), Final Technical Report: Probabilistic performance based durability design of concrete structures, The European Union- BriteEuRam III.
3 El Maaddawy, T. and Soudki, K. (2007), "A model for prediction of time from corrosion initiation to corrosion cracking", Cement Concrete Compos., 29(3), 168-175.   DOI   ScienceOn
4 Engelund, S. and Sorensen, J.D. (1998), "A Probabilistic model for chloride ingress and initiation of corrosion in reinforced Concrete Structures", Struct. Safety, 20, 69-89.   DOI   ScienceOn
5 Fib (CEB-FIP)(2006), Model Code foe Service Life Design.
6 Frangopol, D.M., Lin, K.Y. and Estes, A.C. (1997), "Life-cycle cost design of deteriorating structures", J. Struct. Eng. ASCE, 123, 1390-1401.   DOI   ScienceOn
7 Hagan, M.T., Demuth, H. and Beale, M. (1996), Neural Network Design, PWS Publishing Company.
8 Hornik, K. (1991), "Approximation capabilities of multilayer feedforward networks", Neural Networks, 4(2), 251- 257   DOI   ScienceOn
9 Hurtado, J.E. and Alvarez, D.A. (2001), "Neural network based reliability analysis: A comparative study", Comput. Meth. Appl. Mech. Eng., 191, 113-132   DOI   ScienceOn
10 Hurtado, J.E. (2002), "Analysis of one-dimensional stochastic finite elements using neural networks", Probabil. Eng. Mech., 17, 35-44.   DOI   ScienceOn
11 Papadakis, V.G., Roumeliotis, A.P., Fardis, M.N. and Vagenas, C.G. (1996), "Mathematical modeling of chloride effect on concrete durability and protection measures", (Eds. Dhir, R.K. and Jones, M.R.) Concrete repair, rehabilitation and protection, London.
12 Papadrakakis, M., Papadopoulos, V. and Lagaros, N.D. (1996), "Structural reliability analysis of elastic-plastic structures using neural networks and monte carlo simulation", Comput. Meth. Appl. Mech. Eng., 136, 145-163.   DOI   ScienceOn
13 Poupard, O., L'Hostis, V., Catinaud, S. and Petre-Lazar, I. (2006), "Corrosion damage diagnosis of a reinforced concrete beam after 40 years natural exposure in marine environment", Cement Concrete Res., 36, 504-520.   DOI   ScienceOn
14 Schueller, G.I. (1997), "A state of-the-art report on computational stochastic mechanics", Probabil. Eng. Mech., 12(4),197-231.   DOI   ScienceOn
15 Stewrat, M.G. and Mullard, J.A. (2008), "Spatial time-dependent reliability analysis of corrosion damage and the timing of first repair for RC structures", Eng. Struct, 29(7), 1457-1464
16 Sudret, B., Defaux, G. and Pendola, M. (2007), "Stochastic evaluation of the damage length in RC beams submitted to corrosion of reinforcing steel", Civil Eng. Envir. Syst., 24(2),165-178.   DOI   ScienceOn
17 Sudret, B. and Der Kiureghian, A. (2000), "Stochastic finite element methods and reliability: a state of the art report", Department of Civil and Environmental Engineering University of California, Berkeley.
18 VanMarcke, E. (1984), Random fields, analysis and synthesis, MIT Press.
19 Vu, K.A.T., Stewart, M.G. and Mullard, J. (2005), "Corrosion-induced cracking: experimental data and predictive models", ACI Struct. J., 102(5), 719-726.
20 Vu, K.A.T. and Stewart, M.G. (2005), "Predicting the likelihood and extent of reinforced concrete corrosion-induced cracking", J. Struct. Eng., 131(11), 1681-1689.   DOI   ScienceOn
21 Karimi, A.R., Ramachandran, K. and Buenfeld, N. (2005), "Probabilistic analysis of reinforcement corrosion with spatial variability using random field theory", Proceedings of the Ninth International Conference on Structural Safety and Reliability, ICOSSAR 05. Rome, Italy.
22 Kong, J.K. Ababneh, A.N., Frangopol, D.M. and Xi, Y. (2002), "Reliability analysis of chloride penetration in saturated concrete", Probabil. Eng. Mech., 17, 305-315.   DOI   ScienceOn
23 Li, C. and Der Kiureghian, A. (1993), "Optimal discretization of random fields", J. Eng. Mech. ASCE, 119, 1136-1154.   DOI   ScienceOn
24 Liu, Y. and Weyers, R.E. (1998), "Modeling the time-to-corrosion cracking in chloride contaminated reinforced concrete structures", ACI Mater J., 95(6), 675-181.
25 Li, C.Q. (2003), "Life cycle modeling of corrosion affected concrete structures-propagation", J. Struct. Eng., ASCE, 129(6) ,753-776.   DOI   ScienceOn
26 Li, C.Q., Melchers, R.E. and Zheng J.J. (2006), "Analytical model for corrosion-induced crack width in reinforced concrete structures", ACI Struct. J., 103(4), 479-487.
27 Li, Y., Vrouwenvelder, T., Wijnants, G.H. and Walraven, J. (2004), "Spatial variability of concrete deterioration and repair strategies", Struct.Concrete, 5(3), 121-130.   DOI   ScienceOn
28 McKay, M.D., Conover, W.J. and Beckman, R.J. (1979), "A comparison of three methods for selecting values of input variables in the analysis of the output from a computer code", Technometrics, 21(2), 239-245.
29 Most, T. and Bucher, C. (2007), "Probabilistic analysis of concrete cracking using neural networks and random fields", Probabil. Eng. Mech., 22, 219-229.   DOI   ScienceOn
30 Nataf, A. (1962), "Determination des distributions de probabilities don't les margessontdonnees", ComptesRendus de l'Academie des Sciences, 225, 42-43.
31 Olsson, A., Sandberg, G. and Dahlblom, O. (2003), "On Latin hypercube sampling for structural reliability analysis", Struct. Safety, 25, 47-68.   DOI   ScienceOn
32 Cheng, J, Li, Q.S. and Xiao, R.C. (2008), "A new artificial neural network-based response surface method for structural reliability analysis", J. Struct. Eng. Mech., 23, 51-63.
33 Chryssanthopoulos, M. and Sterritt, G. (2002), "Integration of deterioration modeling and reliability assessment for reinforced concrete bridge structures", First ASRANet international colloquium (CD- ROM).
34 Bentz, E.C. (2003), "Probabilistic modeling of service life for structures subjected to chlorides", ACI Mater. J., 100(5), 391-397.
35 American Concrete Institute, ACI 365 1R-00 (2000), Service Life Prediction, State of the Art Report, Detroit, USA.
36 American Concrete Institute, ACI (2005), Building Code Requirements for Structural Concrete, ACI 318-05, Detroit, USA.
37 Bamforth, P.B. and Price, W.F. (1996), "An international review of chloride ingress into structural concrete", Taywood Engineering Ltd.,Technology Division, Middlesex.
38 Chen, D. and Mahadevan, S. (2008), "Chloride-induced reinforcement corrosion and concrete cracking simulation", Cement Concrete Compos., 30, 227-238.   DOI   ScienceOn