Prediction of external corrosion rate for buried oil and gas pipelines: A novel deep learning method with DNN and attention mechanism-Reference-Cited by-同舟云学术

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Prediction of external corrosion rate for buried oil and gas pipelines: A novel deep learning method with DNN and attention mechanism

Published:2024-06 Issue: Volume:209 Page:105218
ISSN:0308-0161
Container-title:International Journal of Pressure Vessels and Piping
language:en
Short-container-title:International Journal of Pressure Vessels and Piping

Author:

Guang Yu,Wang Wenhe,Song Hongwei,Mi Hongfu,Tang Junlei,Zhao Zebin

Publisher

Elsevier BV

Reference33 articles.

1. Failure mode and the prevention and control technology of buried PE pipeline in service: state of the art and perspectives;Li;Adv. Civ. Eng.,2022

2. Experimental investigation of stress corrosion on supercritical CO2 transportation pipelines against leakage for CCUS applications;Wang;Energy Rep.,2023

3. Time-dependent reliability of corroded mild steel pipes by different failure modes;Zhang;Int. J. Pres. Ves. Pip.,2024

4. External corrosion pitting depth prediction using Bayesian spectral analysis on bare oil and gas pipelines;Balekelayi;Int. J. Pres. Ves. Pip.,2020

5. A novel liquid pipeline internal corrosion direct evaluation technology and the application on the water pipeline;He;Eng. Fail. Anal.,2024

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