Article ID Journal Published Year Pages File Type
7962963 Journal of Nuclear Materials 2018 11 Pages PDF
Abstract
In the present work, a numerical model based on the coupling of Kampmann and Wagner Numerical (KWN) framework and thermodynamic software ThermoCalc has been developed to predict grain boundary precipitate evolution in 316H stainless steel during thermal aging. The model is calibrated and validated against precipitate size distributions obtained by accelerated isothermal heat treatment and analysed using scanning electron microscopy (SEM). Elemental distribution was also investigated using electron microprobe analysis (EPMA). The predicted average particle size, particle size distribution and precipitate number density predicted by the model were found to be in good agreement with the experimental results. The model was then applied to predict the particle size distribution after several years exposure at service temperature. It is demonstrated that these predictions are consistent with measurements from a service-exposed part. The sensitivity of the precipitate size distribution to temperature is emphasised, and it is demonstrated that the model has potential as a useful tool for predicting evolution of the precipitate size distribution during service, providing reliable thermal data are available for the whole service life.
Related Topics
Physical Sciences and Engineering Energy Nuclear Energy and Engineering
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