Identification of Non-Linear Vibration Parameters of a Nuclear Fuel Rod
Bibliographic record
Abstract
In Pressurized Water Reactors (PWR), fuel assemblies are composed of fuel rods, long slender tubes filled with uranium pellets, bundled together using spacer grids. These structures are subjected to fluid-structure interactions, due to the flowing coolant surrounding the fuel assemblies inside the core, coupled with large-amplitude vibrations in case of external seismic excitation. Therefore, understanding the non-linear response of the structure and, particularly, its dissipation, is of paramount importance for the choice of safety margins. To model the nonlinear dynamic response of fuel rods, the identification of nonlinear stiffness and damping parameters is required. The case of a single fuel rod with clamped-clamped boundary conditions was investigated by applying harmonic excitation at various force levels. Different configurations were implemented testing the fuel rod in air and in still water; the effect of metal pellets simulating nuclear fuel pellets inside the rods was also recorded. Non-linear parameters were extracted from some of the experimental response curves by means of a numerical tool based on the harmonic balance method. The axisymmetric geometry of fuel rods resulted in the presence of a one-to-one internal resonance phenomenon, which has to be taken into account modifying accordingly the numerical identification tool. The internal motion of fuel pellets is a cause of friction and impacts, complicating further the linear and non-linear dynamic behavior of the system. An increase of the equivalent viscous-based modal damping with excitation amplitude is often shown during geometrically non-linear vibrations, thus confirming previous experimental findings in the literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".