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Probability distribution model of stress impact factor for corrosion pits of high-strength prestressing wires
Highlights A significant increase of stress concentration was found with increased corrosion. The factor K can be fitted by a Gumbel distribution at a confidence level of 95%. The location factor was found to be more affected by the element length. A relationship was established for the model parameters and degree of corrosion.
Abstract The random distribution of corrosion pits causes the cross-sectional area of a tendon to vary along its length, producing a severe stress concentration at the pits. These effects must be quantified to predict the fatigue life of corroded prestressed concrete beams. The stress impact factor K, which was employed to quantify the combined effects of stress concentration and longitudinal variation of cross-sectional areas, can be used to determine the real stress state around the corrosion pits. This paper proposes a probabilistic model of the stress impact factor for corrosion pits of high-strength prestressing wires. One hundred and forty-three corroded prestressing wire specimens, 400–600 mm in length, were extracted from failed beams in fatigue tests. By using a high accuracy three-dimensional (3D) laser scanning technique, the 3D geometric models of corroded wires were obtained, and then the geometric parameters of corrosion pits and the discrete cross-sectional areas along the length of wires were extracted. Further, a finite element analysis was carried out to determine the stress concentration factor of corroded wires. A significant increase was found in both the longitudinal variation of the cross-sectional area and stress concentration with the development of corrosion. The statistical results indicate that K can be fitted by a minimum Gumbel distribution at a confidence level of 95%. Both the location and scale factors of the distribution model K increased linearly with the increased average degree of corrosion. The location factor of the probability model K was found to be more affected by the element length than the scale factor. The relationship was established between the model parameters of K and the average degree of corrosion for wires with different element lengths, which were in an acceptable agreement with experimental results. In comparison with the existing deterministic analysis models, the proposed probabilistic model of K makes it possible to calculate the probability distribution of residual fatigue life and the failure probability of corroded prestressed concrete beams under fatigue loading.
Probability distribution model of stress impact factor for corrosion pits of high-strength prestressing wires
Highlights A significant increase of stress concentration was found with increased corrosion. The factor K can be fitted by a Gumbel distribution at a confidence level of 95%. The location factor was found to be more affected by the element length. A relationship was established for the model parameters and degree of corrosion.
Abstract The random distribution of corrosion pits causes the cross-sectional area of a tendon to vary along its length, producing a severe stress concentration at the pits. These effects must be quantified to predict the fatigue life of corroded prestressed concrete beams. The stress impact factor K, which was employed to quantify the combined effects of stress concentration and longitudinal variation of cross-sectional areas, can be used to determine the real stress state around the corrosion pits. This paper proposes a probabilistic model of the stress impact factor for corrosion pits of high-strength prestressing wires. One hundred and forty-three corroded prestressing wire specimens, 400–600 mm in length, were extracted from failed beams in fatigue tests. By using a high accuracy three-dimensional (3D) laser scanning technique, the 3D geometric models of corroded wires were obtained, and then the geometric parameters of corrosion pits and the discrete cross-sectional areas along the length of wires were extracted. Further, a finite element analysis was carried out to determine the stress concentration factor of corroded wires. A significant increase was found in both the longitudinal variation of the cross-sectional area and stress concentration with the development of corrosion. The statistical results indicate that K can be fitted by a minimum Gumbel distribution at a confidence level of 95%. Both the location and scale factors of the distribution model K increased linearly with the increased average degree of corrosion. The location factor of the probability model K was found to be more affected by the element length than the scale factor. The relationship was established between the model parameters of K and the average degree of corrosion for wires with different element lengths, which were in an acceptable agreement with experimental results. In comparison with the existing deterministic analysis models, the proposed probabilistic model of K makes it possible to calculate the probability distribution of residual fatigue life and the failure probability of corroded prestressed concrete beams under fatigue loading.
Probability distribution model of stress impact factor for corrosion pits of high-strength prestressing wires
Liu, Xiguang (author) / Zhang, Weiping (author) / Gu, Xianglin (author) / Ye, Zhiwen (author)
Engineering Structures ; 230
2020-12-01
Article (Journal)
Electronic Resource
English
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