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Shannon Entropy Analysis of a Nuclear Fuel Pin Under Deep Burnup
Wojciech R Kubiński1,2, Jan K Ostrowski1, Krzysztof W Fornalski1
1Faculty of Physics, Warsaw University of Technology, ul. Koszykowa 75, 00-662 Warszawa, Poland.
Nuclear fuel entropy shows a U-shaped curve during deep burnup, indicating self-organization and eventual degradation. A minimum entropy point around 45 years may signal a physical limit for fuel utilization in pressurized water reactors (PWRs).
Area of Science:
- Nuclear Engineering
- Information Theory
- Reactor Physics
Background:
- Nuclear fuel behavior under extreme burnup conditions is not fully understood.
- Standard operational ranges for nuclear fuel do not encompass deep burnup scenarios.
- Entropy analysis offers a novel perspective on complex systems like nuclear fuel.
Purpose of the Study:
- To analyze the entropy evolution of nuclear fuel rods under deep burnup conditions (up to 60 years).
- To investigate the relationship between entropy and nuclear fuel behavior, including operational limits.
- To develop and apply a novel scaling method for Monte Carlo simulations of long-life reactors.
Main Methods:
- Monte Carlo method for analyzing neutron source distribution.
- Shannon information entropy for quantifying system complexity.
- A novel scaling method adjusting neutron population based on fission rate for statistical accuracy.
Main Results:
- A "U-shaped" entropy evolution was observed: initial decrease (self-organization), stabilization, then increase (degradation).
- A minimum entropy state, indicating a potential physical limit for fuel utilization, was reached around 45 years of pin operation.
- Post-minimum entropy increase reflects system degradation and reduced energy efficiency.
Conclusions:
- Entropy analysis provides valuable insights into nuclear fuel behavior and operational limits under extreme burnup.
- The identified minimum entropy state may represent a critical threshold for nuclear fuel utilization.
- The proposed scaling method is effective for controlling Monte Carlo simulations, particularly for long-life reactor analyses.
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