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The authors developed an artificial intelligence (AI)-based algorithm for the design and optimization of a nuclear reactor core based on a flexible geometry and demonstrated a 3× improvement in the selected performance metric: temperature peaking factor. The rapid development of advanced, and specifically, additive manufacturing (3-D printing) and its introduction into advanced nuclear core design through the Transformational Challenge Reactor program have presented the opportunity to explore the arbitrary geometry design of nuclear-heated structures. The primary challenge is that the arbitrary geometry design space is vast and requires the computational evaluation of many candidate designs, and the multiphysics simulation of nuclear systems is very time-intensive. Therefore, the authors developed a machine learning-based multiphysics emulator and evaluated thousands of candidate geometries on Summit, Oak Ridge National Laboratory’s leadership class supercomputer. The results presented in this work demonstrate temperature distribution smoothing in a nuclear reactor core through the manipulation of the geometry, which is traditionally achieved in light water reactors through variable assembly loading in the axial direction and fuel shuffling during refueling in the radial direction. The conclusions discuss the future implications for nuclear systems design with arbitrary geometry and the potential for AI-based autonomous design algorithms.

Iron-chromium-aluminum (FeCrAl) alloys are candidates to be used as nuclear fuel cladding for increased accident tolerance. An analysis of the response of FeCrAl under normal operating and loss of coolant conditions has been performed using fuel performance modeling. In particular, recent information on FeCrAl material properties and phenomena from separate effects tests has been implemented in the BISON fuel performance code and analyses of integral fuel rod behavior with FeCrAl cladding have been performed. BISON simulations included both light water reactor normal operation and loss-of-coolant accidental transients. In order to model fuel rod behavior during accidents, a cladding failure criterion is desirable. For FeCrAl alloys, a failure criterion is developed using recent burst experiments under loss of coolant like conditions. The added material models are utilized to perform comparative studies with Zircaloy-4 under normal operating conditions and oxidizing and non-oxidizing out-of-pile loss of coolant conditions. The results indicate that for all conditions studied, FeCrAl behaves similarly to Zircaloy-4 with the exception of improved oxidation performance. Further experiments are required to confirm these observations.