Further development of the gamma exponent model for assessment of flaws in oil and gas pipelines
The Gamma Exponent Model (“GEM”) is a recently developed methodology for failure pressure prediction of flaws in oil and gas pipelines. The model has previously demonstrated applicability for the assessment of axial surface breaking (or “part wall”) cracks and localized metal loss/corrosion. This wo...
Gespeichert in:
Veröffentlicht in: | Journal of Pipeline Science and Engineering 2021-09, Vol.1 (3), p.321-328 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The Gamma Exponent Model (“GEM”) is a recently developed methodology for failure pressure prediction of flaws in oil and gas pipelines. The model has previously demonstrated applicability for the assessment of axial surface breaking (or “part wall”) cracks and localized metal loss/corrosion. This work extends the applicability of the model to circumferential surface cracks. In addition, the GEM is shown to be consistent and complementary to the log-secant model for assessment of axial through wall cracks, developed by the NG18 Committee of the Battelle Institute in the early 1970s. The ongoing development of the GEM raises some important theoretical considerations related to understanding of the stress state at the flaw tip during the failure process. The current industry models are not explicit regarding the plane stress or plane strain conditions at the flaw tip, though this has a significant effect on model development. Analysts often assume plane stress conditions, due to oil and gas pipelines typically being considered “thin wall” pipe. However, this work confirms the theory that surface cracks are subject to plane strain conditions, and the selection of fracture toughness correlations from impact energy data becomes very important. The model is validated against available laboratory, hydrotest and in-service failure data. Statistical analyses demonstrate the mathematical form of the new model is valid. Failure pressure predictions are shown to be improved over current industry models. This can have a significant effect on the reliability pipeline integrity programs and improved efficiency in the form of cost savings. |
---|---|
ISSN: | 2667-1433 2667-1433 |
DOI: | 10.1016/j.jpse.2021.06.002 |