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Title: Modelling and Analysis of the Corrosion Characteristics of Ferritic-Martensitic Steels in Supercritical Water

Journal Article · · Materials
DOI: https://doi.org/10.3390/ma12030409 · OSTI ID:1613929
 [1];  [2];  [2];  [3];  [3];  [2];  [2];  [3];  [3]; ORCiD logo [3];  [3]
  1. Xi'an Jiaotong Univ., Shaanxi (China); Univ. of California, Berkeley, CA (United States); DOE/OSTI
  2. Xi'an Jiaotong Univ., Shaanxi (China)
  3. Univ. of California, Berkeley, CA (United States)

The dependencies of weight gain of 9-12 Cr ferritic-martensitic steels in supercritical water on each of seven principal independent variables (temperature, oxygen concentration, flow rate, exposure time, and key chemical composition and surface condition of steels) have been predicted using a supervised artificial neural network (ANN). The relative significance of each independent variable was uncovered by fuzzy curve analysis, which ranks temperature and exposure time as the most important. The optimized ANN, not only satisfactorily represents the experimentally-known non-linear relationships between the corrosion characteristics of F-M steels and the key independent variables (demonstrating the effectiveness of this technique), but also predicts and reveals that the effects of oxygen concentration on the weight gains, to a certain degree, is influenced by the flow rate and temperature. Finally, according to the ANN predicted-results, departure of oxidation kinetics from the parabolic law, and basic cause of chromium content in steel substrate influencing the corrosion rate, and the synergetic effects of dissolved oxygen concentration, flow rate, and temperature, are discussed and analyzed.

Research Organization:
Univ. of California, Oakland, CA (United States)
Sponsoring Organization:
USDOE Office of Nuclear Energy (NE)
Grant/Contract Number:
NE0008541
OSTI ID:
1613929
Journal Information:
Materials, Journal Name: Materials Journal Issue: 3 Vol. 12; ISSN MATEG9; ISSN 1996-1944
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English

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