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Your search keyword '"V. V. Kovtanyuk"' showing total 2 results
Start Over Author "V. V. Kovtanyuk" Journal corrosion engineering, science and technology
2 results on '"V. V. Kovtanyuk"'

1. Estimation of the long-term corrosion resistance of typical metals in the coastal regions of the Russian Federation

Author

Andrey Marshakov, T. N. Igonin, Yulia Panchenko, L. A. Nikolaeva, and V. V. Kovtanyuk

Subjects
020209 energy, General Chemical Engineering, 02 engineering and technology, General Chemistry, 021001 nanoscience & nanotechnology, Atmospheric sciences, Term (time), The arctic, Corrosion, Atmosphere, Atmospheric corrosion, 0202 electrical engineering, electronic engineering, information engineering, Environmental science, General Materials Science, Black sea, Russian federation, 0210 nano-technology
Abstract

This study reports the characteristics of atmosphere corrosivity parameters on the sea coasts of Russia, namely, on the Arctic and Pacific Oceans and the Black Sea. It gives the results of predicti...

Published
2021
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2. Comparative estimation of long-term predictions of corrosion losses for carbon steel and zinc using various models for the Russian territory

Author

Yu. M. Panchenko, V. V. Kovtanyuk, Andrey Marshakov, T. A. Andryushchenko, T. N. Igonin, and L. A. Nikolaeva

Subjects
Estimation, Materials science, Carbon steel, 020209 energy, General Chemical Engineering, Metallurgy, chemistry.chemical_element, 02 engineering and technology, General Chemistry, Zinc, engineering.material, Corrosion, Term (time), Atmospheric corrosion, chemistry, 0202 electrical engineering, electronic engineering, information engineering, engineering, General Materials Science
Abstract

Based on the results of 1-year tests at 12 sites in the Far Eastern region of Russia, priority dose–response functions (DRFs) that provide the best match with experimental data on corrosion losses for carbon steel and zinc have been selected. Long-term (up to 50 years) predictions of corrosion losses of these metals in the continental territory of Russia have been given. A comparative estimation of the mass loss predictions by priority DRFs and the power–linear model has also been given.

Published
2017
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