TY - GEN
T1 - On the applicability of extreme value statistics in the prediction of maximum pit depth in heavily corroded non-piggable buried pipelines
AU - Alfonso, L.
AU - Caleyo, F.
AU - Hallen, J. M.
AU - Araujo, J.
PY - 2010
Y1 - 2010
N2 - There exists a large number of works aimed at the application of Extreme Value Statistics to corrosion. However, there is a lack of studies devoted to the applicability of the Gumbel method to the prediction of maximum pitting-corrosion depth. This is especially true for works considering the typical pit densities and spatial patterns in long, underground pipelines. In the presence of spatial pit clustering, estimations could deteriorate, raising the need to increase the total inspection area in order to obtain the desired accuracy for the estimated maximum pit depth. In most practical situations, pit-depth samples collected along a pipeline belong to distinguishable groups, due to differences in corrosion environments. For example, it is quite probable that samples collected from the pipeline's upper and lower external surfaces will differ and represent different pit populations. In that case, maximum pitdepth estimations should be made separately for these two quite different populations. Therefore, a good strategy to improve maximum pit-depth estimations is critically dependent upon a careful selection of the inspection area used for the extreme value analysis. The goal should be to obtain sampling sections that contain a pit population as homogenous as possible with regard to corrosion conditions. In this study, the aforementioned strategy is carefully tested by comparing extreme-value-oriented Monte Carlo simulations of maximum pit depth with the results of inline inspections. It was found that the variance to mean ratio, a measure of randomness, and the mean squared error of the maximum pit-depth estimations were considerably reduced, compared with the errors obtained for the entire pipeline area, when the inspection areas were selected based on corrosioncondition homogeneity.
AB - There exists a large number of works aimed at the application of Extreme Value Statistics to corrosion. However, there is a lack of studies devoted to the applicability of the Gumbel method to the prediction of maximum pitting-corrosion depth. This is especially true for works considering the typical pit densities and spatial patterns in long, underground pipelines. In the presence of spatial pit clustering, estimations could deteriorate, raising the need to increase the total inspection area in order to obtain the desired accuracy for the estimated maximum pit depth. In most practical situations, pit-depth samples collected along a pipeline belong to distinguishable groups, due to differences in corrosion environments. For example, it is quite probable that samples collected from the pipeline's upper and lower external surfaces will differ and represent different pit populations. In that case, maximum pitdepth estimations should be made separately for these two quite different populations. Therefore, a good strategy to improve maximum pit-depth estimations is critically dependent upon a careful selection of the inspection area used for the extreme value analysis. The goal should be to obtain sampling sections that contain a pit population as homogenous as possible with regard to corrosion conditions. In this study, the aforementioned strategy is carefully tested by comparing extreme-value-oriented Monte Carlo simulations of maximum pit depth with the results of inline inspections. It was found that the variance to mean ratio, a measure of randomness, and the mean squared error of the maximum pit-depth estimations were considerably reduced, compared with the errors obtained for the entire pipeline area, when the inspection areas were selected based on corrosioncondition homogeneity.
UR - http://www.scopus.com/inward/record.url?scp=80054033923&partnerID=8YFLogxK
U2 - 10.1115/IPC2010-31321
DO - 10.1115/IPC2010-31321
M3 - Contribución a la conferencia
AN - SCOPUS:80054033923
SN - 9780791844236
T3 - Proceedings of the Biennial International Pipeline Conference, IPC
SP - 527
EP - 535
BT - 2010 8th International Pipeline Conference, IPC2010
T2 - 2010 8th International Pipeline Conference, IPC2010
Y2 - 27 September 2010 through 1 October 2010
ER -