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Probabilistic fatigue life prediction of corroded PC beams considering spatial variability of pitting corrosion
Abstract Pitting corrosion intensifies local stress in materials, accelerating the fatigue crack initiation and propagation at the pit root. The randomly distributed corrosion pits can result in fatigue fractures in rebars and wires at non-critical sections, which further increases the fatigue failure probability of structures. However, previous studies have scarcely taken this into account. Here, we propose a novel model for fatigue life prediction of corroded post-tensioned prestressed concrete (PC) beams, considering the spatial variability of pitting corrosion. First, a Weibull distribution model of the pitting factor is developed based on the 3D laser scanning method. Then, the 3D non-Gaussian random field of the pitting factor in PC beams is generated using the inverse Nataf transformation. Next, the 3D pit-induced stress concentration is modeled using pit shape ratios. Following that, the initiation and propagation of fatigue cracks in pitting corroded wires and rebars are considered by the equivalent initial flaw size methodology. Finally, the fatigue analyses of the pitting corroded wires and rebars in all beam elements are conducted step by step until the load-bearing capacity of PC beams becomes lower than the applied load. The proposed prediction model is validated using the experimental data. The results reveal that neglecting the spatial variability of pitting corrosion overestimates the fatigue life of corroded PC beams, especially under high corrosion degrees.
Highlights A fatigue life prediction model of corroded PC beams considering the spatial variability of pitting corrosion is proposed. The 3D random field of the pitting factor and the 3D pit-induced stress concentration are considered in the prediction model. Ignoring the spatial variability of pitting corrosion overestimates the fatigue life of beam, notably under severe corrosion.
Probabilistic fatigue life prediction of corroded PC beams considering spatial variability of pitting corrosion
Abstract Pitting corrosion intensifies local stress in materials, accelerating the fatigue crack initiation and propagation at the pit root. The randomly distributed corrosion pits can result in fatigue fractures in rebars and wires at non-critical sections, which further increases the fatigue failure probability of structures. However, previous studies have scarcely taken this into account. Here, we propose a novel model for fatigue life prediction of corroded post-tensioned prestressed concrete (PC) beams, considering the spatial variability of pitting corrosion. First, a Weibull distribution model of the pitting factor is developed based on the 3D laser scanning method. Then, the 3D non-Gaussian random field of the pitting factor in PC beams is generated using the inverse Nataf transformation. Next, the 3D pit-induced stress concentration is modeled using pit shape ratios. Following that, the initiation and propagation of fatigue cracks in pitting corroded wires and rebars are considered by the equivalent initial flaw size methodology. Finally, the fatigue analyses of the pitting corroded wires and rebars in all beam elements are conducted step by step until the load-bearing capacity of PC beams becomes lower than the applied load. The proposed prediction model is validated using the experimental data. The results reveal that neglecting the spatial variability of pitting corrosion overestimates the fatigue life of corroded PC beams, especially under high corrosion degrees.
Highlights A fatigue life prediction model of corroded PC beams considering the spatial variability of pitting corrosion is proposed. The 3D random field of the pitting factor and the 3D pit-induced stress concentration are considered in the prediction model. Ignoring the spatial variability of pitting corrosion overestimates the fatigue life of beam, notably under severe corrosion.
Probabilistic fatigue life prediction of corroded PC beams considering spatial variability of pitting corrosion
Guo, Zhongzhao (author) / Wang, Lei (author) / Ma, Yafei (author) / Wu, Bitao (author) / Ren, Liang (author) / Gui, Shuirong (author) / Su, Xiaochao (author)
Engineering Structures ; 306
2024-02-18
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2018
| British Library Online Contents | 2018
Damage tolerance approach for probabilistic pitting corrosion fatigue life prediction
| British Library Online Contents | 2001