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Proc. ASME. IPC2022, Volume 1: Pipeline Safety Management Systems; Project Management, Design, Construction, and Environmental Issues; Strain-Based Design and Assessment; Risk and Reliability; Emerging Fuels and Greenhouse Gas Emissions, V001T07A032, September 26–30, 2022
Paper No: IPC2022-87347
... to estimate grade. As part of this work, a supervised classification machine learning (ML) model was developed to predict pipe grade using NDE chemical composition measurements as inputs. While using the ML-based model provides substantial improvement over yield strength (YS) in predicting pipe grade...
Proc. ASME. IPC2010, 2010 8th International Pipeline Conference, Volume 2, 721-729, September 27–October 1, 2010
Paper No: IPC2010-31523
... reality is that some joints can have strengths that fall below this design expectation. This paper considers the implications of changes due to the globalization of the steel and pipe-making industries relative to the historical evolution of classes/grades of steel and their processing in regard...