Computers and Concrete

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A methodology to evaluate corroded RC structures using a probabilistic damage approach

  • Coelho, Karolinne O. (School of Civil Engineering, Architecture and Urban Design, University of Campinas) ;
  • Leonel, Edson D. (Department of Structural Engineering, Sao Carlos School of Engineering, University of Sao Paulo) ;
  • Florez-Lopez, Julio (School of Civil Engineering, Chongqing University)
  • Received : 2021.01.05
  • Accepted : 2021.12.28
  • Published : 2022.01.25
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Abstract

Several aspects influence corrosive processes in reinforced concrete (RC) structures such as environmental conditions, structural geometry and mechanical properties. Since these aspects present large randomnesses, probabilistic models allow a more accurate description of the corrosive phenomena. Besides, the definition of limit states in the reliability assessment requires a proper mechanical model. In this context, this study proposes a straightforward methodology for the mechanical-probabilistic modelling of RC structures subjected to reinforcements' corrosion. An improved damage approach is proposed to define the limit states for the probabilistic modelling, considering three main degradation phenomena: concrete cracking, rebar yielding and rebar corrosion caused either by chloride or carbonation mechanisms. The stochastic analysis is evaluated by the Monte Carlo simulation method due to the computational efficiency of the Lumped Damage Model for Corrosion (LDMC). The proposed mechanical-probabilistic methodology is implemented in a computational framework and applied to the analysis of a simply supported RC beam and a 2D RC frame. Curves illustrate the probability of failure evolution over a service life of 50 years. Moreover, the proposed model allows drawing the probability of failure map and then identifying the critical failure path for progressive collapse analysis. Collapse path changes caused by the corrosion phenomena are observed.

Keywords

Acknowledgement

The financial support from the Brazilian National Council for Scientific and Technological Development (CNPq) is gratefully acknowledged.

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