The ultimate strength of corroded steel plates with pitting corrosion is studied by stochastic FEM in this paper. An automatic 3D Finite Element Method(FEM) computation procedure scripted by MATLAB/ABAQUS/Python is proposed for stochastic solid model of corroded plates. Finishing great amount of stochastic FEM computation, the results of ultimate tensile strength are processed according to principles of probability and mathematical statistics. The three types of steels with different yield ratio are considered. The follow-up tensile tests on 27 specimens selected from MCS are carried out in laboratory. As a result of this study, the ultimate tensile strength of corroded steel plates will decrease by 7% when the corrosion rate increases by 1% in high probability, and the relation between ultimate strength and yield ratio is found as well.

INTRODUCTION

The steel plates used in structures in ocean engineering will be corroded inevitably in the service process. The uniform and pitting corrosion are two types of corrosion considered in marine structures, in which pitting corrosion is usually considered as more hazardous to the safety of marine structures. The target of this paper is focused on ultimate strength of steel plates with pitting corrosion in a reliable and statistics way.

Prior to study corroded structures, the models of pitting corrosion should be determined. There are two ways to build models for pitting corrosion, one is physical model and another is empirical model. The physical model comes from the physiochemical process of corrosion, while the empirical model obtained from observations in laboratory or industry, which will be considered in this paper. Flaks (1977) have studied the equivalent thickness of pitting steel plate and its residual strength, which is a simple and direct reduced model for the pitting corrosion. For further investigation on the basis of probability phenomenological model, some maximum pit depth probability model have been proposed. Melchers (2008), Melchers & Jeffrey (2008) pointed out that, the maximum pitting pit depth can be treated as the extreme distribution (usually Gumbel distribution). The morphology and radius depth of the pits are also studied by Wang et al (2014). Based on the measured data of corrosion of low carbon steel with obvserable larger pit depth pitting, it is shown that Gumbel distribution of the maximum pitting depth is more accurate than using the double probability density model (Melchers R E, 2005) (Melchers R E, 2008) (Melchers R E, Ahammed M, Jeffrey R, 2010) (Melchers R E, 2010). Following their further research on safety assessment of ships, offshore structures and pipelines using theirproposed corrosion model, it is found that their results are quiet acceptable. Therefore, the model proposed by (Melchers R E, Ahammed M, Jeffrey R, 2010) will be adopted and embedded in stochastic FEA of this paper.

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