Skip to main content
Log in

Probabilistic identification of the effects of corrosion propagation on reinforced concrete structures via deflection and crack width measurements

  • Original Article
  • Published:
Materials and Structures Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. 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

    Article  Google Scholar 

  2. Koch GH, Brongers PH, Virmani YP, Payer J (2002) Corrosion costs and preventive strategies in the United States. NACE International, Houston

    Google Scholar 

  3. Tuutti K (1982) Corrosion of steel in concrete. Swedish Cement and Concrete Research Institute, Stockholm

    Google Scholar 

  4. 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

    Article  Google Scholar 

  5. 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

    Article  Google Scholar 

  6. Vidal T, Castel A, Francois R (2004) Analyzing crack width to predict corrosion in reinforced concrete. Cem Concr Res 34(1):165–174

    Article  Google Scholar 

  7. Taha NA, Morsy M (2016) Study of the behavior of corroded steel bar and convenient method of repairing. HBRC J 12(2):107–113

    Article  Google Scholar 

  8. 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

    Article  Google Scholar 

  9. Azad AK, Ahmad S, Azher SA (2007) Residual strength of corrosion-damaged reinforced concrete beams. ACI Mater J 104(1):40–47

    Google Scholar 

  10. Chung L, Paik IK, Cho S, Roh YS (2006) Infrared thermographic technique to measure corrosion in reinforcing bar. Key Eng Mater 321:821–824

    Article  Google Scholar 

  11. 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

    Article  Google Scholar 

  12. 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

    Article  Google Scholar 

  13. 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

  14. 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

    Article  Google Scholar 

  15. 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

    Article  Google Scholar 

  16. 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

    Article  Google Scholar 

  17. 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

    Google Scholar 

  18. Liu T, Weyers R (1998) Modeling the dynamic corrosion process in chloride contaminated concrete structures. Cem Concr Res 28(3):365–379

    Article  Google Scholar 

  19. Yalcyn H, Ergun M (1996) The prediction of corrosion rates of reinforcing steels in concrete. Cem Concr Res 26(10):1593–1599

    Article  Google Scholar 

  20. Vu KA, Stewart MG (2000) Structural reliability of concrete bridges including improved chloride-induced corrosion models. Struct Saf 22(4):313–333

    Article  Google Scholar 

  21. Vu K, Stewart MG, Mullard J (2005) Corrosion-induced cracking: experimental data and predictive models. ACI Struct J 102(5):719

    Google Scholar 

  22. 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

    Article  Google Scholar 

  23. 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

  24. 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

    Article  Google Scholar 

  25. 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

    Article  Google Scholar 

  26. 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

    Article  Google Scholar 

  27. 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

    Article  Google Scholar 

  28. 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

    Article  Google Scholar 

  29. 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

    Article  Google Scholar 

  30. 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

    Article  Google Scholar 

  31. 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

    Article  Google Scholar 

  32. 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

    Article  Google Scholar 

  33. 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

    Article  Google Scholar 

  34. 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

    Article  Google Scholar 

  35. 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

    Article  Google Scholar 

  36. Moehle J (2014) Seismic design of reinforced concrete buildings. McGraw Hill Professional, New York

    Google Scholar 

  37. Soltis LA (1981) Analysis of continuous beams with joint slip. US Dept. of Agriculture, Forest Service, Forest Products Laboratory, Madison

    Book  Google Scholar 

  38. Stroud JR, Katzfuss M, Wikle CK (2016) A Bayesian adaptive ensemble Kalman filter for sequential state and parameter estimation. arXiv preprint

  39. 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

    Article  Google Scholar 

  40. 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

    Article  Google Scholar 

  41. 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

    Article  Google Scholar 

  42. Mancuso C, Bartlett FM (2017) ACI 318-14 criteria for computing instantaneous deflections. ACI Struct J 114(5):1299

    Article  Google Scholar 

  43. 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

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the University Research Board at the American University of Beirut for funding this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to George Saad.

Ethics declarations

Conflict of interest

The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1617/s11527-019-1389-y

Keywords

Navigation