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Probability-Based Performance Degradation Model and Constitutive Model for the Buckling Behavior of Corroded Steel Bars

Author

Listed:
  • Weipeng Weng

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Xu Xie

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Yanyun Lei

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

Abstract

The corrosion of steel bars significantly influences the safety running of concrete bridges. The current bridge design code always ignores the changes in mechanical properties of the materials during their service life which results in an overestimation of the seismic capacity of concrete bridges Therefore, a hysteretic constitutive model that considers the influence of reinforcement corrosion is necessary. This study established a probability-based model for the mechanical property degradation of corroded steel bars using statistical analysis to estimate the mechanical properties under specific corrosion rates. The validity of the proposed degradation model was verified by a series of monotonic tensile tests on corroded steel bars. Moreover, a constitutive model of corroded steel bars based on the Reinforcing Steel Model in OpenSees was obtained. This model considers the influence of corrosion on the slenderness ratio, yield strength, ultimate strength, and elongation. A comparison with the experimental data demonstrated the accuracy of the proposed model. The proposed model is straightforward because its parameters can be predicted using existing research data. The proposed model can provide a basis for the seismic performance evaluation of corroded reinforced concrete (RC) members.

Suggested Citation

  • Weipeng Weng & Xu Xie & Yanyun Lei, 2023. "Probability-Based Performance Degradation Model and Constitutive Model for the Buckling Behavior of Corroded Steel Bars," Sustainability, MDPI, vol. 15(9), pages 1-16, May.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7532-:d:1139268
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