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An Efficient Chloride Ingress Model for Long-Term Lifetime Assessment of Reinforced Concrete Structures Under Realistic Climate and Exposure Conditions

  • Nguyen, Phu Tho (Institute for Research in Civil and Mechanical Engineering/Sea and Littoral Research Institute, CNRS UMR) ;
  • Bastidas-Arteaga, Emilio (Institute for Research in Civil and Mechanical Engineering/Sea and Littoral Research Institute, CNRS UMR) ;
  • Amiri, Ouali (Institute for Research in Civil and Mechanical Engineering/Sea and Littoral Research Institute, CNRS UMR) ;
  • Soueidy, Charbel-Pierre El (Institute for Research in Civil and Mechanical Engineering/Sea and Littoral Research Institute, CNRS UMR)
  • Received : 2016.08.23
  • Accepted : 2017.01.28
  • Published : 2017.06.30

Abstract

Chloride penetration is among the main causes of corrosion initiation in reinforced concrete (RC) structures producing premature degradations. Weather and exposure conditions directly affect chloride ingress mechanisms and therefore the operational service life and safety of RC structures. Consequently, comprehensive chloride ingress models are useful tools to estimate corrosion initiation risks and minimize maintenance costs for RC structures placed under chloride-contaminated environments. This paper first presents a coupled thermo-hydro-chemical model for predicting chloride penetration into concrete that accounts for realistic weather conditions. This complete numerical model takes into account multiple factors affecting chloride ingress such as diffusion, convection, chloride binding, ionic interaction, and concrete aging. Since the complete model could be computationally expensive for long-term assessment, this study also proposes model simplifications in order to reduce the computational cost. Long-term chloride assessments of complete and reduced models are compared for three locations in France (Brest, Strasbourg and Nice) characterized by different weather and exposure conditions (tidal zone, de-icing salts and salt spray). The comparative study indicates that the reduced model is computationally efficient and accurate for long-term chloride ingress modeling in comparison to the complete one. Given that long-term assessment requires larger climate databases, this research also studies how climate models may affect chloride ingress assessment. The results indicate that the selection of climate models as well as the considered training periods introduce significant errors for mid- and long- term chloride ingress assessment.

Keywords

References

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