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In view of the problems of the current modeling methods for the statistical characteristics of matching probability and measurement error, the modeling method of matching probability and measurement error statistical characteristics based on machine learning is proposed. According to the requirements of total sequence matching probability and system matching times, the sequence matching probability is calculated. The measurement error is analyzed in the process of acquisition and matching, and the measurable interference parameters are obtained. According to the analysis results, the mean value of matching measurement error is standardized, and the matching probability and measurement error statistical characteristics are established sex model. The experimental results show that the matching probability and measurement error statistical model of this method has high accuracy, and has good application effect in practical application.

The relationship between the specific surface area (SSA) of rust and the electrochemical behavior of rusted steel under wet–dry acid corrosion conditions was investigated. The results showed that the corrosion current density first increased and then decreased with increasing SSA of the rust during the corrosion process. The structure of the rust changed from single-layer to double-layer, and the γ-FeOOH content decreased in the inner layer of the rust with increasing corrosion time; by contrast, the γ-FeOOH content in the outer layer was constant. When the SSA of the rust was lower than the critical SSA corresponding to the relative humidity during the drying period, condensed water in the micropores of the rust could evaporate, which prompted the diffusion of O2 into the rust and the following formation process of γ-FeOOH, leading to an increase of corrosion current density with increasing corrosion time. However, when the SSA of the rust reached or exceeded the critical SSA, condensate water in the micro-pores of the inner layer of the rust could not evaporate which inhibited the diffusion of O2 and decreased the γ-FeOOH content in the inner rust, leading to a decrease of corrosion current density with increasing corrosion time.

Effect of small content of chromium (Cr) on wet–dry acid corrosion behavior of low alloy steels has been investigated. The results show that the corrosion resistance of the steels increased with increasing Cr content from 0.10 to 0.50 wt%. Higher content of Cr promotes initial corrosion and accelerates the formation of dense and protective rust in long-term corrosion. The enhanced protectiveness of the rust is closely related to its composition. High content of Cr increases the content of amorphous phases and decreases the content of γ-FeOOH in the rust, resulting in the high compactness of the rust and low electrochemical activity in acid condition. Cr dopes in rust and depresses the transformation from amorphous phases to α-FeOOH, as well as the growth process of FeOOH particles, which is responsible for the enhanced compactness of rust in long-term corrosion.

Effects of W and Mo additions on wet-dry acid corrosion behavior of low-alloy steels under different O2 concentrations were investigated. The results showed that W and Mo-containing steels presented excellent wet-dry corrosion resistance under O2 concentrations of both 1 and 5%. The roles of W and Mo played in increasing corrosion resistance of the steels were different. W could improve the thermodynamic stability of the steel substrate, while Mo could promote the formation of protective rust. Interaction between W, Mo and O2 concentration greatly influenced wet-dry acid corrosion of low-alloy steels. W addition was more effective for depressing charge transfer process at the rust/substrate interface and presented higher enhanced effect on increasing corrosion resistance than Mo under O2 concentration of 1%. Mo was more effective on increasing rust compactness and showed higher enhanced effect on increasing corrosion resistance than W under O2 concentration of 5%.

The influence of cold rolling reduction on microstructure and mechanical properties of the TWIP (ttwinning induced plasticity) steel was investigated. The results indicated that the steel had better comprehensive mechanical properties when cold rolling reduction was about 65.0% and the annealing temperature was 1000°C. The tensile strength of the steel is about 640MPa and the yield strength is higher than 255MPa, while the elongation is above 82%. The microstructure is composed of austenitic matrix and annealing twins at room temperature, at the same time, a significant amount of annealing twins and stacking faults are observed by transmission electron microscopy (TEM). Mechanical twins play a dominant role during deformation, and result in excellent mechanical properties.