Physics-informed reinforcement learning optimization of nuclear assembly design
Optimization of nuclear fuel assemblies if performed effectively, will lead to fuel efficiency improvement, cost reduction, and safety assurance. However, assembly optimization involves solving high-dimensional and computationally expensive combinatorial problems. As such, fuel designers’ expert jud...
| Main Authors: | , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Published: |
Elsevier BV
2021
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| Online Access: | https://hdl.handle.net/1721.1/130571 |