Quantitative Characterization of the Spatial Distribution of Corrosion Pits Based on Nearest Neighbor Analysis

Adeyinka Abass*, Kentaro Wada, Hisao Matsunaga, Heikki Remes, Tiina Vuorio

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
120 Downloads (Pure)

Abstract

Nearest neighbor analysis (NNA)-based procedures are proposed for the quantitative characterization of the spatial distribution of corrosion pits in metals. After the exposure of a carbon steel to a 3.5% NaCl solution mist, the results derived from observation of corrosion pit initiation and growth were used to justify the applicability of this approach. The pits initially comprised clusters that were superimposed on a randomly distributed background set. The clustered pits subsequently coalesced, evolving into a more random pit arrangement. Furthermore, it was revealed that in the early stages, the spatial pit distribution can be predicted via inspection of surface inclusions prior to the corrosion process.

Original languageEnglish
Pages (from-to)861-870
Number of pages10
JournalCorrosion
Volume76
Issue number9
Early online date27 Jun 2020
DOIs
Publication statusPublished - Sept 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • corrosion fatigue
  • environmental effects
  • inclusion
  • pitting corrosion
  • statistics
  • steel
  • COOPERATIVE STOCHASTIC-BEHAVIOR
  • LOCALIZED CORROSION
  • PITTING CORROSION
  • STAINLESS-STEEL
  • INTERGRANULAR CORROSION
  • FATIGUE
  • SITES
  • STATISTICS
  • INITIATION
  • PARTICLES

Fingerprint

Dive into the research topics of 'Quantitative Characterization of the Spatial Distribution of Corrosion Pits Based on Nearest Neighbor Analysis'. Together they form a unique fingerprint.

Cite this