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Title Big Data Approach Application for Steel Pipelines in the Conditions of Corrosion Fatigue
Other Titles Застосування підходу Big Data для сталевих трубопроводів в умовах корозійної втоми
Authors Skrynkovskyy, R.M.
Yuzevych, L.V.
Ogirko, O.I.
Pawlowski, G.
Keywords gas pipeline
monitoring
fatigue crack
corrosion
databases
Big Data
neural network
intelligent software
hardware
газопровід
моніторинг
трищіна втоми
корозія
бази даних
великі дані
нейронна мережа
інтелектуальне програмне забезпечення
апаратні засоби
Type Article
Date of Issue 2018
URI http://essuir.sumdu.edu.ua/handle/123456789/69194
Publisher Sumy State University
License
Citation Big Data Approach Application for Steel Pipelines in the Conditions of Corrosion Fatigue [Текст] / R.M. Skrynkovskyy, L.V. Yuzevych, O.I. Ogirko, G. Pawlowski // Журнал інженерних наук. - 2018. - Т. 5, № 2. - С. Е27-Е32. - DOI: 10.21272/jes.2018.5(2).e6.
Abstract This paper presents results of the use of Big Data approach and neural network for the pipelines diagnosis problem. In this case the pipeline is in the conditions of crack growth of corrosion fatigue and exposed to hydrogen. It is proposed to use graphene protective coatings. The mathematical model for estimating the changes in the effective surface energy of WPL during plastic deformation, electrochemical overstrain, polarization potential and current density of the metal dissolution reaction at the top of the crack on the pipeline surface during its mechanical loading in an aqueous electrolyte solution is given. The dissolution of the metal is considered on the juvenile surface, taking into account the anode and cathode regions based on the approaches of surface physics and electrochemistry. An element of a mathematical model is a quality functional, taking into account information flows and a sensitivity coefficient. Functional quality is used to specify the feedback between the investment project methodology and risk estimates, as well as to optimize the information flows of enterprises and improve the system of protection of metallic underground pipelines that operate under conditions of corrosion fatigue. The purpose of this project is to improve the relevant regulatory and technical documents as well as software.
У роботі подано результати використання підходів Big Data та нейронних мереж для діагностування трубопроводів. Метою цього проекту є вдосконалення відповідних нормативів та технічних документів, а також програмного забезпечення.
Appears in Collections: Journal of Engineering Sciences / Журнал інженерних наук

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