Abstract
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.
Highlights
Energy, especially electricity, plays a vital role in our modern industrial society and in our current civilization
Using artificial neural network (ANN) modelling and fuzzy curve analysis, this paper aims to explore the effects of various independent variables on the weight gain of 9-12Cr F-M steels in supercritical water, and to categorize the importance of each independent variable to the output
Special emphasis are given to discussion and analyses on the departure of oxidation kinetics from the classical parabolic law, the role and method of chromium in hindering the outward transport of metal cations, and the synergetic effects of dissolved oxygen concentration, flow rate, and temperature
Summary
Especially electricity, plays a vital role in our modern industrial society and in our current civilization. Using ANN modelling and fuzzy curve analysis, this paper aims to explore the effects of various independent variables (temperature, chromium content, oxygen concentration, flow rate, composition and surface conditions of steels) on the weight gain of 9-12Cr F-M steels in supercritical water, and to categorize the importance of each independent variable to the output. On this basis, special emphasis are given to discussion and analyses on the departure of oxidation kinetics from the classical parabolic law, the role and method of chromium in hindering the outward transport of metal cations, and the synergetic effects of dissolved oxygen concentration, flow rate, and temperature
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