Near neutral pH Stress Corrosion Cracking (NNpHSCC) associated with external corrosion of pipelines is an issue facing industry today. Determining areas of NNpHSCC susceptibility is crucial to developing Integrity Management Programs and inspection dig schedules. This research involved collecting pertinent field data (inspection dig reports, failure reports, loading histories) and developing a predictive model to help identify areas and lines most susceptible to NNpHSCC. The predictive model focused on the loading history (in this case, SCADA data) patterns to classify different groups of loading conditions. Hydrogen has been identified and established in previous literature to be a major contributor to NNpHSCC. Different Hydrogen Enhancement Factors (HEF) were applied based on how the mechanisms of hydrogen embrittlement react to the respective loading conditions. The predictive model illustrated a dormancy behaviour, similar to the one seen in field conditions and a mechanically activated growth dependent on both hydrogen and previous loading scenarios. A correlation was shown between a limited field sampling and the predicted values. Further improvements and calibrations can be made with the gathering of more field data and continued experimental validation. Once this validation has been performed, this model has the possibility to illustrate what loading conditions increase a segments susceptibility to NNpHSCC.

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