Abstract
This study presents a probabilistic framework for accurate prediction of the impacts of corrosion propagation on reinforced concrete (RC) structures. The presented framework uses the ensemble Kalman filter (EnKF) coupled with easily acquired measurements of corrosive crack widths and mid-span deflection increases for identifying and calibrating corrosion propagation models. The calibrated models are consequently used to forecast the extent of corrosion propagation in RC structures. To assess the efficacy of the presented framework, data corresponding to the long-term chloride-induced corrosion experiments initiated in 1984 at “Laboratoire des Materiaux et Durabilite des Constructions” (L.M.D.C.) in Toulouse, south-west France are used. The results accentuate the robustness of the presented EnKF approach by being able to identify and calibrate candidate corrosion propagation models capable of predicting, with reasonable accuracy, the experimental measurements of corrosive crack width and mid-span deflection in RC members.
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References
Qiao G, Xiao H, Sun G (2011) Identification of the reinforcing steel’s corrosion state in RC beams based on electrochemical sensor. Sens Rev 31:218–227
Koch GH, Brongers PH, Virmani YP, Payer J (2002) Corrosion costs and preventive strategies in the United States. NACE International, Houston
Tuutti K (1982) Corrosion of steel in concrete. Swedish Cement and Concrete Research Institute, Stockholm
Slika W, Saad G (2016) An ensemble Kalman filter approach for service life prediction of reinforced concrete structures subject to chloride-induced corrosion. Constr Build Mater 115:132–142
Siamphukdee K, Collins F, Zou R (2013) Sensitivity analysis of corrosion rate prediction models utilized for reinforced concrete affected by chloride. J Mater Eng Perform 22(6):1530–1540
Vidal T, Castel A, Francois R (2004) Analyzing crack width to predict corrosion in reinforced concrete. Cem Concr Res 34(1):165–174
Taha NA, Morsy M (2016) Study of the behavior of corroded steel bar and convenient method of repairing. HBRC J 12(2):107–113
Shayanfar M-A, Barkhordari M-A, Ghanooni-Bagha M (2015) Probability calculation of rebars corrosion in reinforced concrete using CSS algorithms. J Cent South Univ 22(8):3141–3150
Azad AK, Ahmad S, Azher SA (2007) Residual strength of corrosion-damaged reinforced concrete beams. ACI Mater J 104(1):40–47
Chung L, Paik IK, Cho S, Roh YS (2006) Infrared thermographic technique to measure corrosion in reinforcing bar. Key Eng Mater 321:821–824
Kobayashi K, Banthia N (2011) Corrosion detection in reinforced concrete using induction heating and infrared thermography. J Civ Struct Health Monit 1(2):25–35
Baek S, Xue W, Feng M, Kwon S (2012) Nondestructive corrosion detection in RC through integrated heat induction and IR thermography. J Nondestruct Eval 2(31):181–190
Akiyama M, Frangopol D (2012) Estimation of steel weight loss due to corrosion in RC members based on digital image processing of X-ray photogram. In: Proceedings of the 3rd international symposium on life-cycle civil engineering, Vienna, Austria
Itty P, Serdar M, Meral C, Parkinson D, MacDowell A, Bjegović D et al (2014) In situ 3D monitoring of corrosion on carbon steel and ferritic stainless steel embedded in cement paste. Corros Sci 83:409–418
Michel A, Pease B, Geiker M, Stang H, Olesen J (2011) Monitoring reinforcement corrosion and corrosion-induced cracking using non-destructive X-ray attenuation measurements. Cem Concr Res 41(11):1085–1094
Ahmad S, Bhattacharjee B (1995) A simple arrangement and procedure for in situ measurement of corrosion rate of rebar embedded in concrete. Corros Sci 37(5):781–791
Alghamdi S, Ahmad S (2014) Service life prediction of RC structures based on correlation between electrochemical and gravimetric reinforcement corrosion rates. Cem Concr Compos 8:47–94
Liu T, Weyers R (1998) Modeling the dynamic corrosion process in chloride contaminated concrete structures. Cem Concr Res 28(3):365–379
Yalcyn H, Ergun M (1996) The prediction of corrosion rates of reinforcing steels in concrete. Cem Concr Res 26(10):1593–1599
Vu KA, Stewart MG (2000) Structural reliability of concrete bridges including improved chloride-induced corrosion models. Struct Saf 22(4):313–333
Vu K, Stewart MG, Mullard J (2005) Corrosion-induced cracking: experimental data and predictive models. ACI Struct J 102(5):719
Alonso C, Andrade C, Gonzalez J (1988) Relation between resistivity and corrosion rate of reinforcements in carbonated mortar made with several cement types. Cem Concr Res 18(5):687–698
Otieno M, Beushausen H, Alexander M (2011) Prediction of corrosion rate in RC structures—a critical review. Modelling of corroding concrete structures, Springer, pp 15–37
El Hassan J, Bressolette P, Chateauneuf A, El Tawil K (2010) Reliability-based assessment of the effect of climatic conditions on the corrosion of RC structures subject to chloride ingress. Eng Struct 32(10):3279–3287
Li CQ, Lawanwisut W, Zheng J (2005) Time-dependent reliability method to assess the serviceability of corrosion-affected concrete structures. J Stuct Eng 131(11):1674–1680
Faroz SA, Pujari N, Ghosh S (2016) Reliability of a corroded RC beam based on Bayesian updating of the corrosion model. Eng Struct 126:457–468
Hackl J, Kohler J (2016) Reliability assessment of deteriorating reinforced concrete structures by representing the coupled effect of corrosion initiation and progression by Bayesian networks. Struct Saf 62:12–23
Evensen G (1994) Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J Geophys Res Oceans 29(C5):10143–10162
Vidal T, Castel A, Francois R (2007) Corrosion process and structural performance of a 17 year old reinforced concrete beam stored in chloride environment. Cem Concr Res 37(11):1551–1561
Zhang R, Castel A, Francois R (2009) Serviceability limit state criteria based on steel–concrete bond loss for corroded reinforced concrete in chloride environment. Mater Struct 42(10):1407
Zhu W, Francois R (2014) Corrosion of the reinforcement and its influence on the residual structural performance of a 26-year-old corroded RC beam. Constr Build Mater 51:461–472
Otieno M, Alexander M, Beushausen H-D (2010) Corrosion in cracked and uncracked concrete—influence of crack width, concrete quality and crack reopening. Mag Concr Res 62(6):393–404
Zhu W, Francois R (2015) Structural performance of RC beams in relation with the corroded period in chloride environment. Mater Struct 48(6):1757–1769
Lee H-S, Cho Y-S (2009) Evaluation of the mechanical properties of steel reinforcement embedded in concrete specimen as a function of the degree of reinforcement corrosion. Int J Fract 157:81–88
Yalciner H, Sensoy S, Eren O (2012) Effect of corrosion damage on the performance level of a 25-year-old reinforced concrete building. Shock Vib 19(5):891–902
Moehle J (2014) Seismic design of reinforced concrete buildings. McGraw Hill Professional, New York
Soltis LA (1981) Analysis of continuous beams with joint slip. US Dept. of Agriculture, Forest Service, Forest Products Laboratory, Madison
Stroud JR, Katzfuss M, Wikle CK (2016) A Bayesian adaptive ensemble Kalman filter for sequential state and parameter estimation. arXiv preprint
Khalil M, Sarkar A, Adhikari S, Poirel D (2015) The estimation of time-invariant parameters of noisy nonlinear oscillatory systems. J Sound Vib 344:81–100
Zhang R, Castel A, Francois R (2009) The corrosion pattern of reinforcement and its influence on serviceability of reinforced concrete members in chloride environment. Cem Concr Res 39(11):1077–1086
Slika W, Saad G (2018) Probabilistic identification of chloride ingress in reinforced concrete structures: polynomial chaos Kalman filter approach with experimental verification. J Eng Mech 144(6):04018037
Mancuso C, Bartlett FM (2017) ACI 318-14 criteria for computing instantaneous deflections. ACI Struct J 114(5):1299
Bisaillon P, Sandhu R, Khalil M, Pettit C, Poirel D, Sarkar A (2015) Bayesian parameter estimation and model selection for strongly nonlinear dynamical systems. J Nonlinear Dyn 82:1061–1080
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The authors would like to acknowledge the University Research Board at the American University of Beirut for funding this study.
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Bichara, L., Saad, G. & Slika, W. Probabilistic identification of the effects of corrosion propagation on reinforced concrete structures via deflection and crack width measurements. Mater Struct 52, 89 (2019). https://doi.org/10.1617/s11527-019-1389-y
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DOI: https://doi.org/10.1617/s11527-019-1389-y