Improving the diagnostics of underground pipelines at oil­and­gas enterprises based on determining hydrogen exponent (PH) of the soil media applying neural networks

Improving the diagnostics of underground pipelines at oil­and­gas enterprises based on determining hydrogen exponent (PH) of the soil media applying neural networks

A set of key parameters and information flows has been formed to simulate stages of probing the outside surface of underground metal pipelines (UMP) taking into account pH of the soil contacting with the pipe metal. Specimens of 17G1S steel placed in acid, alkaline and neutral media were examined u...

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Bibliographic Details
Main Authors: Larysa Yuzevych, Ruslan Skrynkovskyy, Volodymyr Yuzevych, Vitalii Lozovan, Grzegorz Pawlowski, Mykhailo Yasinskyi, Ihor Ogirko
Format: Article
Language:English
Published: PC Technology Center 2019-08-01
Series:Eastern-European Journal of Enterprise Technologies
Subjects:
underground pipelines
oil-and-gas enterprises
corrosion currents
polarization potential
hydrogen exponent
neural network
Online Access:http://journals.uran.ua/eejet/article/view/174488

Internet

http://journals.uran.ua/eejet/article/view/174488

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