Computers and Concrete

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Fuzzy methodology application for modeling uncertainties in chloride ingress models of RC building structure

  • Do, Jeongyun (Faculty of Architectural and Urban, Chonbuk National University) ;
  • Song, Hun (Korea Institute of Construction Technology) ;
  • So, Seungyoung (Faculty of Architectural and Urban, Chonbuk National University) ;
  • Soh, Yangseob (Faculty of Architectural and Urban, Chonbuk National University)
  • Received : 2004.12.14
  • Accepted : 2005.08.07
  • Published : 2005.08.25
⟨ Previous Next ⟩

Abstract

Chloride ingress is a common cause of deterioration of reinforced concrete located in coastal zone. Modeling the chloride ingress is an important basis for designing reinforced concrete structures and for assessing the reliability of an existing structure. The modeling is also needed for predicting the deterioration of a reinforced structure. The existing deterministic solution for prediction model of corrosion initiation cannot reflect uncertainties which input variables have. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. There are a lot of prediction model for predicting the time of reinforcement corrosion of structures exposed to chloride-induced corrosion environment. In this work, RILEM model formula and Crank's solution of Fick's second law of diffusion is used. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters instead of random variables of probabilistic modeling of Monte Carlo Simulation and the fuzziness of the time to corrosion initiation is determined by the fuzzy arithmetic of interval arithmetic and extension principle. An analysis is implemented by comparing deterministic calculation with fuzzy arithmetic for above two prediction models.

Keywords

References

  1. AIJ (2004), Recommendations for Durability Design and Construction Practice of Reinforced Concrete, (In English version).
  2. Ciampoli, M. (1999), "A probabilistic methodology to assess the reliability of deteriorating structural elements", Comput. Methods Appl. Mech. Eng., 168, 207-220. https://doi.org/10.1016/S0045-7825(98)00141-8
  3. Do, Jeongyun, et al. (2004), "On the implementation of fuzzy arithmetical operation for prediction model equation of corrosion initiation", Int. J. Korea Concrete Institute.
  4. Do, Jeongyun, et al. (2004), "Nominal cover thickness design of RC quantitatively considering environment condition by means of fuzzy inference system", J. Asian Architecture and Building Engineering, 3(2).
  5. George, J. Klir and Bo Yuan, Fuzzy Sets and Fuzzy Logic (1995), Theory and Application, Prentice-Hall Inc., New Jersey, USA.
  6. Hanss, M., et al. (2000), "On the implementation of fuzzy arithmetical operations for engineering problems", Proc. of the 17th International Conference of the North American Fuzzy Information Processing Society- NAFIPS, Pensacola Beach, USA, 365-369.
  7. Hanss, M., et al. (2002), "Simulation and analysis of structural joint models with uncertainties", Proc. of the International Conference on Structural Dynamics Modeling -- Test, Analysis, Correlation and Validation, Madeira Island, Portugal, pp. 165-174.
  8. Jbebe, A. J., Guinot, V. and Solomatine, D. P. (2000), "Fuzzy alpha-cut vs. Monte Carlo techniques in assessing uncertainty in model parameters", Proc. 4th International conference on Hydroinformatics, Iowa City, USA, July.
  9. JSCE (2002), Standard Code for Concrete, 2002.
  10. Kirkpatrick, T. J., et al. (2002), "Probabilistic model for the chloride-induced corrosion service life of bridge decks", Cement and Conc. Res., 32, 1943-1960. https://doi.org/10.1016/S0008-8846(02)00905-5
  11. Lounis, Z. (2001), Decision Support Tools for Life Prediction and Rehabilitation of Concrete Bridge Decks, APWA International Public Works Congress, Philadelphia, pp. 67-77.
  12. Martin-Perez, B. (1999), "Service life modeling of RC highway structures exposed to chlorides", Ph.D. Thesis, Department of Civil Engineering, University of Toronto.
  13. Miyagawa, T. (1985), Early Chloride Corrosion of Reinforcing Steel in Concrete, University of Kyoto.
  14. Otsuki, N. Yokoi, T. and Shimozawa, O. (1985), "The influence of chloride on the passivation film on the surface of steel bars in mortar", Proc. of JSCE, 360, 111-118.
  15. RILEM REPORT 14, Durability Design of Concrete Structure, 1996. Thoft-Christensen, P. (2001), "What happens with reinforced concrete structures when the reinforcement corrodes", Proc. I. Workshop on Life-Cycle Cost Analysis and Design of Civil Infrastructure Systems, Ube, Yamaguchi, Japan, .
  16. Thoft-Christensen, P. (2002), "Deterioration of concrete Structures", First International Conference on Bridge Maintenance, Safety and Management, Barcelona.
  17. Tuuti, K. (1982), Corrosion of Steel in Concrete, Swedish Cement and Concrete Research Institute, 17-21.
  18. Weyers, R. E. Prowell, B., Sprinkel, M. M. and Vorster, M. (1993), "Concrete bridge protection, repair, and rehabilitation relative to reinforcement corrosion: A methods application manual", SHRP-S-360, Strategic Highway Research Program, Washington DC.
  19. Zabokrtsky, Z. (2002) Constrained Fuzzy Arithmetic Engineer's View, Research Report, Czech Technical University.

Cited by

  1. Transient meshless boundary element method for prediction of chloride diffusion in concrete with time dependent nonlinear coefficients vol.36, pp.2, 2012, https://doi.org/10.1016/j.enganabound.2011.08.005
  2. Neuro-fuzzy based prediction of the durability of self-consolidating concrete to various sodium sulfate exposure regimes vol.5, pp.6, 2008, https://doi.org/10.12989/cac.2008.5.6.573
  3. On the Implementation of Fuzzy Arithmetic for Prediction Model Equation of Corrosion Initiation vol.17, pp.6, 2005, https://doi.org/10.4334/jkci.2005.17.6.1045