Abstract
The estimates of critical component life predicted by structural integrity assessments dictate how reliably a nuclear power plant can safely supply electricity to the grid. As such, ensuring these assessments give the most accurate life prediction, whilst remaining safe, is of great importance to both the customer as well as electricity provider. In current structural assessment methodologies safe operation is ensured by incorporating significant conservative factors; especially in areas prone to failure such as welds.If the over-conservative nature could be reduced whilst maintaining confidence then the life of current plants could be extended, increasing the economic benefit of power stations, as well as allowing for more accurate analysis for future designs.
Crystal plasticity finite element (CPFE) modelling represents a potential method for improving predictions because it considers the local microstructure, something not directly examined by current methods.
In this thesis, the ability of CPFE to predict mechanical behaviour at temperatures often seen by in-service components is investigated and the results are compared to current industrial lifing methods.
The CPFE prediction of mechanical behaviour is compared with those measured by scanning electron microscopy experiments for validation. Additionally, demonstrating the influence of often neglected factors is considered; namely pre-test intra-granular residual stress fields and the sub-surface microstructure.
The previously investigated CPFE model is also used to give a life prediction of a case study. This life prediction is compared to a R5 structural assessment hand-calculation and an inelastic model prediction of the same case study. This last analysis highlights how CPFE is able to predict similar life to current continuum assessment methods whilst also being able to account for microstructural variation in the material response.
| Date of Award | 1 Oct 2024 |
|---|---|
| Original language | English |
| Awarding Institution |
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| Supervisor | Mahmoud Mostafavi (Supervisor) & David M Knowles (Supervisor) |
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