Development of CAN^2 (Canister Corrosion Analysis, Assessment, and ActioN PlaNs), a Predictive Detection and Interpretation Software Platform for Life-Cycle Management of Spent Fuel Canisters

When nuclear reactor performance drops below desired energy levels, the radioactive waste must be properly disposed. Until deep geological disposal sites are identified for very long-term storage of this waste (1000’s of years), interim storage methods must be used for much longer than initially intended (~100 years). With 1000’s of dry storage canisters presently loaded with spent nuclear fuel and more loaded each year, reactor sites and canister vendors must properly address aging effects in their aging management programs to ensure canister longevity. The primary objective of this work is to develop and deliver a web-based machine learning software tool that addresses aging effects for optimizing life-cycle decisions and ensuring long-term performance of welded stainless-steel dry storage canisters for the storage of spent nuclear fuel. Incorporating this tool into daily operations will promote pro-active decision-making and improved risk management to minimize the likelihood of a potentially catastrophic, failure event (i.e. loss of the canister’s containment boundary). The outcome of Phase I was a fully-functioning prototype software tool that successfully demonstrated the feasibility of the approach, including: (i) a web-based user-interface and online database to satisfy the workflow requirements of the end-users, (ii) the artificial intelligence Bayesian decision network engine, and (ii) the chloride-induced stress corrosion cracking model with supporting experimental data. Even though the Phase I prototype software is all encompassing and predictive, assumptions were made in populating the engine, and configuring the user-interface. During Phase II efforts, these assumptions will be relaxed to improve predictability and reduce uncertainty. Efforts will also focus on further anchoring the engine into the fundamentals of the damage mechanisms, as well as refinement, verification, validation, and commercialization of both the engine and the web-based user-interface and online database, to ensure market-readiness.