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Probabilistic modeling of reinforced concrete bond behavior considering failure mode and corrosion
Bond at the rebar-concrete interface plays a critical role in the structural performance of reinforced concrete (RC) structures. This bond behavior is typically described by a bond stress-slip relationship, where there are two critical quantities: bond strength ̶ the maximum shear stress that bond can withstand, and peak slip ̶ the slippage at the interface when the bond strength is reached. It is understood that the bond deteriorates when corrosion is present and behaves differently under two distinct bond failure modes (i.e. splitting and pull-out). Thus, this study aims to develop probabilistic prediction models for bond strength and peak slip under the two bond failure modes considering corrosion. In particular, multivariate nonlinear regression with all-possible subset model selection and symbolic multi-gene regression are adopted for the model development. The results show that the developed models outperform other existing models, and also provide satisfactory flexural behavior predictions when they are applied to RC beams.
Probabilistic modeling of reinforced concrete bond behavior considering failure mode and corrosion
Bond at the rebar-concrete interface plays a critical role in the structural performance of reinforced concrete (RC) structures. This bond behavior is typically described by a bond stress-slip relationship, where there are two critical quantities: bond strength ̶ the maximum shear stress that bond can withstand, and peak slip ̶ the slippage at the interface when the bond strength is reached. It is understood that the bond deteriorates when corrosion is present and behaves differently under two distinct bond failure modes (i.e. splitting and pull-out). Thus, this study aims to develop probabilistic prediction models for bond strength and peak slip under the two bond failure modes considering corrosion. In particular, multivariate nonlinear regression with all-possible subset model selection and symbolic multi-gene regression are adopted for the model development. The results show that the developed models outperform other existing models, and also provide satisfactory flexural behavior predictions when they are applied to RC beams.
Probabilistic modeling of reinforced concrete bond behavior considering failure mode and corrosion
Soraghi, Ahmad (author) / Huang, Qindan (author)
Structure and Infrastructure Engineering ; 20 ; 263-285
2024-02-01
23 pages
Article (Journal)
Electronic Resource
English
Probabilistic Model for Rebar-Concrete Bond Failure Mode Prediction Considering Corrosion
| British Library Conference Proceedings | 2019