Hydrodynamic Coupling Forces in the ZED-2 Research Reactor
Bibliographic record
Abstract
Abstract Vibration-induced neutron noise in nuclear reactors may reveal abnormal vibrations in reactor core internals. To investigate this correlation, an experimental program was undertaken at the Zero Energy Deuterium (ZED-2) nuclear research reactor at Canadian Nuclear Laboratories (CNL). The plan was to attach a neutron-absorbing plate to one of the vertical hanging fuel channels and induce it to vibrate using a small under-water shaker. However, this would also induce unwanted vibration of the connected fuel channel and also in the neighbouring fuel channel because of fluid coupling. This was a safety concern that required investigation. Hence, an experimental study was conducted on a reduced scale mock up of the reactor, consisting of a round tank of water with a 5x5 inline square tube array of tubes that were suspended and partially submerged in the water. The central tube was unique in that it was mounted on a pivot and the upper end was connected to an electrodynamic shaker (i.e., the “exciter” tube). The surrounding “passive” tubes were suspended from a common support, and five of those were instrumented with strain gauges to measure the hydrodynamically coupling vibration responses induced by the vibration of the central exciter tube. This evaluation aimed to quantify the cross-coupling forces between the exciter tube and the surrounding instrumented passive tubes. The measurements were applied to the ZED-2 reactor to estimate the hydrodynamic coupling forces between a vibrating fuel channel and its nearest neighbours. A numerical model was developed to determine the resulting fuel channel displacements, and time domain simulations were performed to estimate the fuel channel responses in the ZED-2 reactor. The numerical analysis is used to define the safe test parameters for the subsequent vibration-induced neutron noise experiments in ZED-2.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".