Use of Statistical Analysis Methods for Estimating the Reliability of First-Year Carbon Steel and Zinc Corrosion Loss Predictions Calculated Using Dose-Response Functions
- Authors: Panchenko Y.M.1, Marshakov A.I.1, Bardin I.V.1, Shklyaev A.V.2
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Affiliations:
- Frumkin Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences
- Moscow State University
- Issue: Vol 55, No 4 (2019)
- Pages: 753-760
- Section: Physicochemical Problems of Materials Protection
- URL: https://journals.rcsi.science/2070-2051/article/view/205393
- DOI: https://doi.org/10.1134/S2070205119040142
- ID: 205393
Cite item
Abstract
The following parameters have been used to estimate the reliability of predicted first-year corrosion losses of carbon steel and zinc (\(K_{1}^{{{\text{pr}}}}\)): the standard determination coefficient \(R_{{{\text{st}}}}^{2}\) according to ASTM G 16; statistical indicators such as SMAPE and MAPE; generalized determination coefficients; confidence angle. The experimental data on corrosion losses of carbon steel and zinc (\(K_{1}^{{{\text{exp}}}}\)) and the atmosphere corrosivity parameters were taken from the UN/ECE international program and Russian program. The \(K_{1}^{{{\text{pr}}}}\) values were calculated using various dose-response functions. It is not recommended to use the standard determination coefficient \(R_{{{\text{st}}}}^{2}\) in the y = \(K_{1}^{{{\text{pr}}}},\)x = \(K_{1}^{{{\text{exp}}}}\) coordinates.
Keywords
About the authors
Yu. M. Panchenko
Frumkin Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences
Email: mar@ipc.rssi.ru
Russian Federation, Moscow, 119071
A. I. Marshakov
Frumkin Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences
Author for correspondence.
Email: mar@ipc.rssi.ru
Russian Federation, Moscow, 119071
I. V. Bardin
Frumkin Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences
Email: mar@ipc.rssi.ru
Russian Federation, Moscow, 119071
A. V. Shklyaev
Moscow State University
Email: mar@ipc.rssi.ru
Russian Federation, Moscow, 119991
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