Reliability of steam generator is a serious concern in the operation of nuclear power plants, especially for steam generator tubes that experience a variety of degradation mechanisms including wear damage. It is necessary to develop a model to accurately predict wear depth of tubes for the assessment and management of steam generator aging. In this article, a non-homogeneous Markov process model of wear is proposed to assess the evaluation of wear depth in steam generator tubes. Based on the analytical solutions of the system of Kolmogorov's forward equations, the transition probability functions are computed to estimate the future wear depth distribution. The parameters are estimated under the assumption that the mean wear depths in the proposed Markov stochastic model are equal to the average of measured depths. The time evolution of wear depth distribution can be predicted. The proposed Markov stochastic model was tested with the in-service inspection records from steam generator tube inspection report, and the results showed a good agreement with future wear depth distribution.

The fatigue crack growth (FCG) behavior of 34CrMo4 steel, a typical material for gas cylinders, has been investigated. Specimens were taken from the base material (BM) as well as the hot-drawn (HD) cylinder and cold-flow (CF) formed cylinder along the longitudinal and transverse directions. The FCG tests were conducted under different stress ratios for different materials and directions. The main purpose of this research was to explore the influences of the mechanical and thermal processes, sampling direction and stress ratio on the FCG behavior of 34CrMo4 steel. To further reveal the mechanism of crack propagation at different stages, the microstructures and fracture modes of FCG specimens were analyzed by scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), respectively. The results showed that HD and CF materials exhibited better resistance to fatigue crack propagation than BM. The FCG rates of investigated materials can be accelerated by the increase in stress ratio. However, the sampling direction had little effect on the FCG rate. Finally, a driving force parameter (DFP) model was used to fit the experimental FCG data of three materials with different mechanical and thermal processes. A unified transition stage between the stable and unstable FCG stages of three materials under various experimental conditions was revealed by DFP model, playing an important role on the early warning of fatigue fracture for different types of 34CrMo4 steel.