Skip to main content
Article
Localized Corrosion Risk Assessment Using Markov Analysis
Corrosion: The Jounral of Science and Engineering
  • K McCallum, University of Akron Main Campus
  • J Zhao, University of Akron Main Campus
  • M Workman, University of Akron Main Campus
  • M Iannuzzi, University of Akron Main Campus
  • M Kappes, University of Akron Main Campus
  • Joe Payer, University of Akron Main Campus
  • Curtis B. Clemons, University of Akron Main Campus
  • S Chawla
  • Kevin L. Kreider, University of Akron Main Campus
  • Nao Mimoto, University of Akron Main Campus
  • Gerald W Young, The University Of Akron
Document Type
Article
Publication Date
11-1-2014
Disciplines
Abstract
The objective of this work was to develop the foundation for an interactive corrosion risk management tool for assessing the probability of failure of equipment/infrastructure as a function of threats (such as pitting corrosion and coating degradation) and mitigation schemes (such as inhibitors and coatings). The application of this work was to assist with corrosion management and maintenance planning of equipment/infrastructure given dynamic changes in environmental conditions. Markov models are developed to estimate pitting damage accumulation density distributions as a function of input parameters for pit nucleation and growth rates. The input parameters are selected based upon characterization with experimental or field observations over a sufficiently long period of time. Model predictions are benchmarked against laboratory pitting corrosion tests and long-term atmospheric exposure data for aluminum alloys, obtained from the literature. The models are also used to examine hypothetical scenarios for the probability of failure in pipeline systems subject to sudden, gradual, and episodic events that change the corrosive conditions.
Citation Information
K McCallum, J Zhao, M Workman, M Iannuzzi, et al.. "Localized Corrosion Risk Assessment Using Markov Analysis" Corrosion: The Jounral of Science and Engineering Vol. 70 Iss. 11 (2014) p. 1114 - 1127
Available at: http://works.bepress.com/nao_mimoto/1/