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Keywords: machine learning
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Proceedings Papers

Proc. ASME. IPC2020, Volume 1: Pipeline and Facilities Integrity, V001T03A068, September 28–30, 2020
Paper No: IPC2020-9331
... be that the estimated depth of a feature is 36%wt in an interval of [30%, 48%] of wall thickness with 80% confidence. This is believed to greatly reduce the level of uncertainty when it comes to failure pressure estimation or other type of pipeline risk assessment. The advancement in Machine Learning today, deep...
Proceedings Papers

Proc. ASME. IPC2020, Volume 1: Pipeline and Facilities Integrity, V001T03A078, September 28–30, 2020
Paper No: IPC2020-9624
...NOW YOU SCC ME, NOW YOU DON T USING MACHINE LEARNING TO FIND STRESS CORROSION CRACKING Michael Smith, Aidan Blenkinsop, Matthew Capewell, Brian Kerrigan ROSEN Group, Newcastle upon Tyne, United Kingdom ABSTRACT Electromagnetic Acoustic Transducer (EMAT) is a non-destructive inspection technology...