Nonlinear Vibrations of Model PWR Fuel Assemblies: Part 1 — Experimental Setup and Measurements
Bibliographic record
Abstract
Abstract Nuclear fuel bundles in PWR reactors present vibrations due to coolant flow, which may result in fretting at the interface between the fuel rods and the retaining elements, named spacer grids (SGs). Seismic excitation may also occur during accidental events, such as earthquakes. In this perspective, forced vibration experiments were performed on a reduced-scale nuclear fuel bundle provided by Framatome Canada. The presence of partially loose fuel pellets inside the fuel rods was provided in the experiments. A maximum coolant flow of 5 meters per second was reached inside a water tunnel. The identification of vibration parameters was attempted in the linear regime, through modal analysis, and in the nonlinear regime, through a single-degree-of-freedom method based on harmonic balance. The value of the equivalent damping parameter was shown to increase strongly with the amplitude of the excitation, thus acting in the direction of safety. The fuel bundle presents a peculiar softening vibration behavior in the nonlinear regime, with a marked decrease of the peak vibration frequency. The comparison with other recent experiments shows that the boundary conditions constituted by SGs have a predominant effect on stiffness and damping during nonlinear vibrations. Therefore, the characterization of the boundary conditions at the SGs was attempted by means of dedicated experiments. Bending oscillations were tested in the frequency range between DC and 50 Hertz. Tests were repeated in presence and in absence of water. The resulting force-displacement loops clearly show the presence of hysteresis and of bilinear stiffness. The availability of a mathematical model for the stiffness and the damping at the boundary conditions will be indispensable for the future development of reduced-order models describing the vibrations of PWR fuel bundles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".