Abstract
We apply the MOOSE framework's optimization module to Hierarchical Shape Optimization for a PWR fuel assembly design, adaptively optimizing the fuel pin's shape. Accounting for changes in neutronics behavior is captured with cross section generation in Serpent while changes in heat transfer is considered by dynamically updating convective heat transfer coefficients during the optimization process. We employ the derivative-free Nelder-Mead algorithm to optimize the fuel pin geometry, demonstrating notable improvements in performance metrics. The hierarchical approach avoids local minima by gradually increasing geometric complexity, achieving a final keff improvement of 1390 pcm over the non-hierarchical baseline.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the TopFuel 2025 |
| Subtitle of host publication | Nuclear Reactor Fuel Performance Conference |
| Publisher | American Nuclear Society |
| Pages | 1228-1237 |
| Number of pages | 10 |
| ISBN (Electronic) | 9780894482281 |
| DOIs | |
| State | Published - 2025 |
| Externally published | Yes |
| Event | TopFuel 2025: Nuclear Reactor Fuel Performance Conference - Nashville, United States Duration: Oct 5 2025 → Oct 9 2025 |
Publication series
| Name | Proceedings of the TopFuel 2025: Nuclear Reactor Fuel Performance Conference |
|---|
Conference
| Conference | TopFuel 2025: Nuclear Reactor Fuel Performance Conference |
|---|---|
| Country/Territory | United States |
| City | Nashville |
| Period | 10/5/25 → 10/9/25 |
Funding
This research used funding received from the DOE Office of Nuclear Energy's Nuclear Energy University Program under grant project number 22-26770.
Keywords
- Hierarchical
- MOOSE
- Optimization
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