4.6 Article

Experimental and numerical analysis of mechanical behaviors of long-term atmospheric corroded Q235 steel

期刊

STRUCTURES
卷 39, 期 -, 页码 115-131

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.istruc.2022.03.027

关键词

Atmospheric corrosion; Corrosion morphology; Residual strength; Ductility; Pitting model considering fusion

资金

  1. National Natural Science Foundation of China [51708384]
  2. Natural Science Foundation of Shanxi Province [201901D211017, 202103021224047]
  3. Science and Technology Project for Oversea Scholars in Shanxi Province [DC1900000602]

向作者/读者索取更多资源

This study quantitatively analyzed the degradation of corroded Q235 steel through microscopic and tensile tests. It was found that corrosion pits significantly reduce the strength and ductility of the steel. A new pitting model was proposed to more accurately count and measure the pits, and predict strength degradation.
In the present study, microscopic and tensile tests are carried out on specimens corroded in the atmosphere for 33 years to quantitatively analyze the degradation of corroded Q235 steel. Results show that the mass loss ratio of steel members can reach up to 0.1309. Also, it was found that the pit depth and aspect ratio obey the Gaussian distribution with their mean values of 0.396 and 0.219, respectively. Corrosion pits significantly reduce the yield strength, ultimate strength, elastic modulus, and ductility, among which the elongation is reduced by up to 24.51%. In addition, a new pitting model, in which the pitting fusion is included, is presented. It will be shown that this model can more accurately count and measure pits. Based on this model, a numerical parameter analysis of steel members with random pits is conducted using the ABAQUS software and NumPy package in Python software. New nonlinear relationships between mass loss ratio and strengths are proposed to better explain the effects of variation of stress concentration caused by corrosion pits evolution. Also, it will be shown that this model can be used to predict the strength degradation more accurately.

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