Numerical analysis of pit-to-crack transition under corrosion fatigue using a stochastic pit generation algorithm

TL;DR

This paper investigates how the complex, randomly-shaped pits caused by corrosion affect fatigue crack initiation in marine structures, using a stochastic algorithm to generate realistic pit geometries for numerical analysis.

Contribution

It introduces a stochastic pit generation algorithm to model irregular corrosion pits and compares the effects of realistic versus simplified geometries on fatigue analysis results.

Findings

Complex pit morphology significantly influences stress distribution.

Simplified models may underestimate fatigue crack initiation risk.

Stochastic modeling improves accuracy of corrosion fatigue predictions.

Abstract

Corrosion fatigue is a major threat to the integrity of marine structures. However, the combined damaging effect of corrosion and fatigue is not well understood due to the uncertainties associated with the stochastic nature of pitting corrosion. A pitting corrosion defect could have a quite complex morphology that varies randomly from one case to another. Nevertheless, in numerical corrosion fatigue studies, the complex pit morphology is often idealized using an overly simplified geometry with a smooth surface because of the diffi-culties involved in modelling defects with the irregular and random shapes of pitting corrosion. The present study investigates the influence of such geometrical simplifications on the results of numerical corrosion fatigue analyses. For this purpose, an isolated complex-shaped pit, generated using a hierarchical stochastic algorithm scripted in Python and linked with Abaqus/CAE, is developed in a Q235 steel dog-bone specimen. The numer-ical results obtained from this model are compared with those from another model containing an idealized counterpart of the irregular pit. A discussion on the effect of pit morphology on the stress/strain history and distribution and fatigue crack initiation is presented.