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

Yanhui Li; Tongtong Xu; Shuzhong Wang; Balazs Fekete; Jie Yang; Jianqiao Yang; Jie Qiu; Aoni Xu; Jiaming Wang; Yi Xu; Digby  D. Macdonald

doi:10.3390/ma12030409

Materials (Jan 2019)

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

Yanhui Li,
Tongtong Xu,
Shuzhong Wang,
Balazs Fekete,
Jie Yang,
Jianqiao Yang,
Jie Qiu,
Aoni Xu,
Jiaming Wang,
Yi Xu,
Digby D. Macdonald

Affiliations

Yanhui Li: Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Tongtong Xu: Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Shuzhong Wang: Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Balazs Fekete: Departments of Nuclear Engineering & Materials Science and Engineering, University of California at Berkeley, Berkeley, CA 94720, USA
Jie Yang: Departments of Nuclear Engineering & Materials Science and Engineering, University of California at Berkeley, Berkeley, CA 94720, USA
Jianqiao Yang: Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Jie Qiu: Departments of Nuclear Engineering & Materials Science and Engineering, University of California at Berkeley, Berkeley, CA 94720, USA
Aoni Xu: Departments of Nuclear Engineering & Materials Science and Engineering, University of California at Berkeley, Berkeley, CA 94720, USA
Jiaming Wang: Departments of Nuclear Engineering & Materials Science and Engineering, University of California at Berkeley, Berkeley, CA 94720, USA
Yi Xu: Departments of Nuclear Engineering & Materials Science and Engineering, University of California at Berkeley, Berkeley, CA 94720, USA
Digby D. Macdonald: Departments of Nuclear Engineering & Materials Science and Engineering, University of California at Berkeley, Berkeley, CA 94720, USA

DOI: https://doi.org/10.3390/ma12030409
Journal volume & issue: Vol. 12, no. 3
p. 409

Abstract

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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.

Published in Materials

ISSN: 1996-1944 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering; Technology: Engineering (General). Civil engineering (General); Science: Natural history (General): Microscopy; Science: Physics: Descriptive and experimental mechanics
Website: http://www.mdpi.com/journal/materials/

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