Modeling Pit Growth as a Function of Environmental Variables Through Stochastic Approaches

It is well known that rates of pitting corrosion damage are influenced by environmental variables such as applied potential, temperature, and concentrations of ions in solution. Regression methods have often been used to estimate the maximum pit depth as a function of environmental parameters. In th...

Full description

Saved in:
Bibliographic Details
Published inCorrosion (Houston, Tex.) Vol. 75; no. 2; pp. 210 - 216
Main Authors Kralovec, Carrie, Navidi, William, Shayer, Zeev
Format Journal Article
LanguageEnglish
Published Houston NACE International 01.02.2019
Subjects
Corrosion
Corrosion potential
Corrosion rate
Depth
Environmental factors
Lifetime
Materials Science
Metallurgy & Metallurgical Engineering
Methods
Nuclear fuels
Parameters
Pitting (corrosion)
Probability distribution
Probability theory
Simulation
Statistical analysis
Stochasticity
Online AccessGet full text

Cover

More Information
Summary:It is well known that rates of pitting corrosion damage are influenced by environmental variables such as applied potential, temperature, and concentrations of ions in solution. Regression methods have often been used to estimate the maximum pit depth as a function of environmental parameters. In this paper, regression methods are used both to predict the maximum depth and to estimate the probability distribution of the maximum depth at a future time. It is shown that these predictions can be reasonably accurate (within 15% of the true value) even when the true mathematical relationships between pitting rates and environmental parameters are nonlinear, and in some circumstances when future values of the environmental variables are not known.
Bibliography:USDOE Office of Nuclear Energy (NE)
NE0008442
ISSN:0010-9312
1938-159X
DOI:10.5006/3017