Estimativa da profundidade de pite em arames de aço carbono utilizado em armaduras de risers flexíveis utilizando o método de queda de potencial, simulação numérica e python

Abstract

Pitting corrosion in the tensile armours of flexible risers poses a critical safety challenge to the offshore industry, requiring accurate and non-destructive inspection techniques. This work proposes the development of a hybrid methodology for predicting pit depth, integrating the Potential Drop technique, Finite Element Analysis (FEA), and numerical interpolation algorithms. To this end, the behavior of the helical wire of flexible risers was modeled using COMSOL Multiphysics software, generating a database correlating surface current density with defect depth. A computational algorithm was developed in Python, employing cubic spline interpolation to estimate damage severity based on electrical readings. Experimental validation was performed on a specimen containing a controlled defect, machined with a diameter of 4.8 mm and a depth of 2.00 mm. During the Potential Drop test, this pitting scenario resulted in a current density reading of 0.1337 A/mm². The results demonstrated the tool's effectiveness, estimating a depth of 1.88 mm with a relative error of only 5.77%. Additionally, the application of Cheriet’s severity criterion confirmed the methodology’s robustness in decision-making, correctly classifying both the real and predicted defects in the same Severe Damage category. It is concluded that the tool developed for this case offers a reliable solution for integrity monitoring, capable of converting electrical signals into dimensionais diagnoses.