Ricker, R.
(2010),
Analysis of Pipeline Steel Corrosion Data From NBS (NIST) Studies Conducted Between 1922-1940 and Relevance to Pipeline Management, Journal of Research (NIST JRES), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/jres.115.026
(Accessed December 12, 2024)
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Analysis of Pipeline Steel Corrosion Data From NBS (NIST) Studies Conducted Between 1922-1940 and Relevance to Pipeline Management
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Abstract
Between 1922 and 1940, the National Bureau of Standards (NBS) conducted a study into the corrosion of bare steel and wrought iron pipes buried underground at 47 sites representing different soil types across the Unites States. Following the passage of the Pipeline Safety Improvement Act, the Office of Pipeline Safety requested that the National Institute of Standards and Technology (NBS became NIST in 1988) reexamine this data to determine if modern computers, software, and statistical analyses could extract more meaningful information from these data. The data from the original NBS studies were analyzed using commercially available software packages for statistical analysis. Linear regression and curve fitting of the corrosion damage measurements against the measured soil compositions and properties identified trends that improved with multiple regression analysis. Empirical equations representing the performance were developed with uncertainty estimates. The uncertainties in these empirical models were relatively large and extrapolations will create additional uncertainties. It is concluded that empirical relationships can be developed from data of this type, but more complete datasets with information on the composition and properties of the soil directly in contact with the samples acquired in statistically designed experiments would greatly reduce uncertainties and enable more representative predictions.Citation
Journal of Research (NIST JRES) -
Volume
115
Issue
5
NIST Pub Series
Pub Type
NIST Pubs
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Keywords
corrosion, underground, soil, pipeline, steel, pitting, empirical model
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Created October 29, 2010, Updated June 2, 2021