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  • 标题:Markov stochastic process modeling for evolution of wear depth in steam generator tubes
  • 本地全文:下载
  • 作者:Xing He ; Xiaojiao Xu ; Wei Tian
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2019
  • 卷号:11
  • 期号:5
  • 页码:1-9
  • DOI:10.1177/1687814019846256
  • 出版社:Sage Publications Ltd.
  • 摘要: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.
  • 关键词:Non-homogeneous Markov process;time evolution;wear depth;steam generator tubes
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