Abstract
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...
Highlights
Steam generator (SG) tubes in nuclear power plants play an important safety role in transferring heat and isolating the radioactive products in the primary coolant from the secondary system
Ten-thousand Ushaped tubes are installed in a typical SG of pressurized water reactors, which are supported at intermediate points by tube support plates (TSPs) in the straight-leg region and by anti-vibration bars (AVBs) in the Ubend region.[1]
A non-homogeneous Markov process model of wear is proposed to assess the evaluation of wear depth in SG tubes
Summary
Steam generator (SG) tubes in nuclear power plants play an important safety role in transferring heat and isolating the radioactive products in the primary coolant from the secondary system. Large number of research works can be found on the wear coefficient from the view point of material properties.[6,7] Not surprisingly, most results indicate that wear coefficient presents to be disperse, which affected by the material itself and the service conditions.[8,9,10] Another challenge with wear depth evaluation is that it is hard to compute the work rate that depends on dynamic characteristics of SG tubes under multiphase fluid.[11] it is difficult to evaluate the accurate wear depth on wear mechanism during the operation of nuclear power plants Recognizing these situations, a strategy for the assessment of SG tube integrity based on the theory of probability and statistics is studied and adopted in engineering practice.[12] The approach utilizes the data of in-service inspection (ISI) by non-destructive examination (NDE) to determine degradation growth rate, which is regarded as a random variable. If the initial damage state is ni at t = ti, so that D(ti) = ni, the time-dependent stochastic mean of the wear depth for the linear growth Markov process can be expressed as.
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