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The development of new nuclear reactor structural and fuel materials is critical to extending and improving the performance of existing reactors as well as the development of next generation reactors. However, due to safeguards and regulations, the implementation of novel and advanced reactor materials requires an expensive and time consuming qualification and licensing process, which may take decades to receive final approval. An accelerated nuclear reactor materials qualification campaign aimed at shortening the nuclear reactor materials qualification timeline down to five to ten years is currently under way. The accelerated qualification of these materials requires an in depth understanding of the thermomechanical behavior under reactor conditions through accelerated irradiation experiments, various in situ and ex situ characterization techniques, separate effects investigation, and performance testing. This comprehensive data collection effort may then be coupled with advanced computational methodologies such as artificial intelligence algorithms, computational performance codes, and digital twins, which can down select and optimize material components and predict material performance after many years of operation, resulting in a significantly more efficient roadmap to the deployment of new nuclear reactor materials.
This symposium focuses on studies, both computational and experimental, aimed at the accelerated qualification of nuclear reactor structural and fuel materials.
Abstracts are encouraged for the following topic areas (but not limited to):
• Accelerated neutron, proton, and heavy ion irradiation experiments
• In-situ and ex-situ experiments and characterization which simulate and evaluate materials exposed to in-reactor conditions of existing and advanced reactor concepts
• Opportunities and obstacles in regulatory acceptance of accelerated materials qualification campaigns
• Computational studies including, modeling, machine learning, and artificial intelligence aimed at predicting performance after extended reactor core exposure
• Advancements and developments of digital twin programs in the nuclear materials domain
• Computational studies aimed at more efficiently down selecting and optimizing material components |