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.

The effect of chloride concentration on the passivity breakdown of carbon steel in deaerated pH = 13.5 alkaline solution was investigated. The results show that chloride plays an important role for the pitting corrosion of carbon steel. When NaCl ≤ 1 M , the carbon steel is passive but for 1 M < NaCl < 2 M , the carbon steel transfers from passive to passivity breakdown. When NaCl ≥ 2 M , passive film breakdown occurs and the passivity breakdown potential ( E _b ) of carbon steel is linearly-dependent on the logarithm of the chloride activity in the alkaline solution. As predicted by the PDM, the near-normal distribution of E b is well indicated by the near straight line in the cumulative distribution probability. The analysis in this study gives us a method to calculate the E b of carbon steel in alkaline solution and its distribution for any given chloride concentration.