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International Journal of Steel Structures

Erschienen in:

10.01.2023

Probabilistic Tensile Strength Model of Q345 Steel Plates with Random Pitting Corrosion for Fragility Analysis

verfasst von: Xu Liao, Xian Li, Yu-Ming Xu

Erschienen in: International Journal of Steel Structures | Ausgabe 2/2023

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Abstract

To evaluate the fracture behavior of steel structures under some severe corrosion environments, experiments on eight artificially pitting corroded Q345 steel plates and numerical investigations on 200 finite element models of randomly pitting damaged steel were conducted. The effects of the distribution, diameter and depth of the corrosion pits on the tensile behavior were investigated and a probability density function of randomly pitting corroded steel strength was developed. The results indicate that both the yield strength and the ultimate strength of steel plates with random pitting corrosion were lower than those of uniformly corroded steels with the same corrosion ratios. The effects of pitting depth on the yield strength and the ultimate strength were more significant than those of pitting diameter. The influences of pitting distribution on ultimate strength were greater than that on yield strength. The residual tensile strength of steel plates with random pitting corrosion was found to well conform to the Gamma distribution, and thus the probability density functions of the residual yield strength and the ultimate strength were proposed based on the Gamma distribution.

Vorheriger Artikel Experimental Investigation of Repair of Plate with Edge and Center Crack by Surface Bounded Composite Patch

Nächster Artikel Effect of Rotational Restraint on Inelastic Buckling of Steel Column at Elevated Temperatures

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Titel: Probabilistic Tensile Strength Model of Q345 Steel Plates with Random Pitting Corrosion for Fragility Analysis
verfasst von: Xu Liao
Xian Li
Yu-Ming Xu
Publikationsdatum: 10.01.2023
Verlag: Korean Society of Steel Construction
Erschienen in: International Journal of Steel Structures / Ausgabe 2/2023
Print ISSN: 1598-2351
Elektronische ISSN: 2093-6311
DOI: https://doi.org/10.1007/s13296-023-00709-3

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