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Life time extension of turbine rotating components under risk constraints: A state-of-the-art review and case study

  • Xuefei Guan*
  • , Jingjing He
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a methodology for life time extension of turbine rotating components under risk constraints subject to fatigue crack damage. A state-of-the-art review is given to reveal the historical perspective and the current practice of life time extension. The evaluation of the fatigue life of these components is highly important to mechanical integrity, and in many cases is centered on the ultrasonic inspection data and fracture mechanics. Due to the inherent uncertainty and stochastic nature of the fatigue crack propagation, the remaining life assessment needs to incorporate various uncertainties for risk mitigation. Among the uncertainties, the sizing uncertainty of an embedded crack is significant because the crack cannot be directly accessed and need to be assessed indirectly using ultrasonic inspection. The assessment result is uncertain owing to the unknown orientation of the crack and inspection competency. This uncertainty can be quantified by correlating the actual flaw size and the reported flaw size. This study investigates the method of extending the fatigue life by scientific quantification and minimization of this uncertainty. By analyzing the sizing performance based on the previous sizing data and the present sizing data using the method of model-assisted probability of detection, the life extension can be realized without compromising the risk requirement in a probabilistic framework. The overall method is demonstrated using a realistic steam turbine rotor with actual ultrasonic inspection data.

Original languageEnglish
Article number104799
JournalInternational Journal of Fatigue
Volume129
DOIs
StatePublished - Dec 2019

Keywords

  • Fatigue crack growth
  • Life time extension
  • Non-destructive evaluation
  • Probability of detection
  • Risk

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