Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Bayesian model updating for the corrosion fatigue crack growth rate of Ni-base alloy X-750

  • Received : 2020.03.26
  • Accepted : 2020.06.15
  • Published : 2021.01.25
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Abstract

Nickel base Alloy X-750, which is used as fastener parts in light-water reactor (LWR), has experienced many failures by environmentally assisted cracking (EAC). In order to improve the reliability of passive components for nuclear power plants (NPP's), it is necessary to study the failure mechanism and to predict crack growth behavior by developing a probabilistic failure model. In this study, The Bayesian inference was employed to reduce the uncertainties contained in EAC modeling parameters that have been established from experiments with Alloy X-750. Corrosion fatigue crack growth rate model (FCGR) was developed by fitting into Paris' Law of measured data from the several fatigue tests conducted either in constant load or constant ΔK mode. These parameters characterizing the corrosion fatigue crack growth behavior of X-750 were successfully updated to reduce the uncertainty in the model by using the Bayesian inference method. It is demonstrated that probabilistic failure models for passive components can be developed by updating a laboratory model with field-inspection data, when crack growth rates (CGRs) are low and multiple inspections can be made prior to the component failure.

Keywords

Acknowledgement

This research was a part of the project titled 'Development of the safety standards for marine hydrogen storage vessels and fuel supply systems', funded by the Ministry of Oceans and Fisheries, Korea. This work was also financially supported by the Material and Component Fusion Alliance (No. 1415166303) of the Ministry of Trade, Industry and Energy, Korea.

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