Modeling fatigue-assisted pitting in pipeline steel with PCA-XFEM

Abstract

We present a localized corrosion and cracking damage mechanism (initiation of the pit, propagation of the pit, pit-to-crack transition, and stable cracking) in a pipeline steel under the application of fatigue loading by using sequential coupling of Probabilistic Cellular Automata (PCA) and eXtended Finite Element Method (XFEM). PCA is utilized for describing the localized corrosion damage mechanism. XFEM is used to simulate arbitrary inhomogeneities (cracks, voids, and soft/hard material interfaces (inclusions)) with the help of Level Set Methods (LSM). In the XFEM, the standard finite element is enriched by additional degrees of freedom by invoking the notion of the partition of unity, which alleviates the burden of mesh conformity to the internal boundaries and avoids re-meshing. LSM is used to locate the voids and material interfaces and track the crack propagation location. A localized strain criterion initiates cracks from the pit surface when the pit reaches a critical strain value.The coupling of PCA and XFEM demonstrates good agreement with experimental data regarding stress-assisted pitting corrosion and pit-induced fatigue cracking in the pipeline steel. The study also investigates the effects of boundaries, and initial pit size on fatigue crack initiation and growth. Boundary effects significantly influence crack initiation life and growth behavior, highlighting the importance of considering both defect characteristics and boundary conditions in assessing fatigue performance and structural integrity. Various initial pit sizes and geometric features further affect crack initiation location and transition time. Furthermore, the PCA-XFEM model effectively captures crack behavior in both short and long crack regimes, demonstrating good agreement with experimental data for a selected pit width of 140μm. By incorporating crack driving parameters derived from experiments, the model accurately predicts crack propagation, further enhancing its reliability and predictive capabilities in assessing fatigue crack behavior. Overall, this approach provides valuable insights for predicting the service life and integrity of pipelines subjected to similar loading conditions, thus aiding in designing and maintaining these critical infrastructure components.