Corrosion and Materials Degradation (Jun 2024)

Review of the Modelling of Corrosion Processes and Lifetime Prediction for HLW/SF Containers—Part 2: Performance Assessment Models

  • Fraser King,
  • Miroslav Kolàř,
  • Scott Briggs,
  • Mehran Behazin,
  • Peter Keech,
  • Nikitas Diomidis

DOI
https://doi.org/10.3390/cmd5020013
Journal volume & issue
Vol. 5, no. 2
pp. 289 – 339

Abstract

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The disposal of high-level radioactive waste (HLW) and spent nuclear fuel (SF) presents a unique challenge for the prediction of the long-term performance of corrodible structures since the HLW/SF canisters are expected, in some cases, to have lifetimes of one million years or longer. Various empirical and deterministic models have been developed over the past 45 years for making predictions of the long-term corrosion behaviour, including models for uniform and localized corrosion, environmentally assisted cracking and microbiologically influenced corrosion. As well as process models focused on specific corrosion mechanisms (described in Part 1 of this review), there is also a need for performance assessment models as part of the overall analysis of the safety of a deep geological repository (DGR). Performance assessment models are often based on simplified or abstracted process models. The manner in which various international waste management programs have predicted the long-term performance of HLW/SF containers with copper, steel, Ni and Ti alloy corrosion barriers is discussed. Performance assessments are repeated periodically during the development and implementation of a DGR, and the corrosion models are constantly updated in light of new mechanistic understanding and/or more information about the deep geological environment. Two examples of how the container performance assessment models evolve over time are also described. Performance assessment models cannot easily be validated, so it is important to build confidence in the long-term predictions using other methods, including natural analogues and large-scale in situ tests and the use of complementary models.

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