Bayesian analysis of external corrosion data of non-piggable underground pipelines. (January 2015) - Caleyo, F.; Valor, A.; Alfonso, L.; Vidal, J.; Perez-Baruch, E.; Hallen, J.M.
Highlights: A Bayesian methodology for the analysis of external corrosion data is presented. It uses corrosion data samples taken at ditch sites along the inspected pipeline. From them, the distributions of the corrosion defect size and density are estimated. An 80% confidence is attained with 60 corrosion defects in 15 excavation sites. Detection and measurement errors can be incorporated for direct assessment applications. Abstract: A new Bayesian methodology for the analysis of external corrosion data of non-piggable underground pipelines has been developed. It allows for the estimation of the statistical distributions of the density and size of external corrosion defects from corrosion data samples taken at excavation sites along the inspected pipeline and can incorporate the detection and measurement errors associated with field inspections. Corrosion data obtained from field inspections of an upstream pipeline and from an in-line inspection of a transportation pipeline are used to illustrate and validate the proposed methodology.