Dynamics of CANDU fuel bundles
Bibliographic record
Abstract
One of the most important parts of a nuclear reactor is the fuel bundle in which the nuclear reaction takes place and heat is generated. The heat is transported through the flow of the coolant to the steam generator. During such process, the fuel bundles are subjected to severe operation conditions, such as highly turbulent coolant flow, high temperatures and excessive irradiation doses. These severe conditions significantly affect the integrity of the fuel bundle in terms of flow-induced vibrations (FIV). The FIV are produced by various excitation mechanisms such as, the turbulence buffeting, the fluidelastic forces (Motion-dependent forces) and the acoustic pressure pulsations coming from the primary heat pump. In the current study, a numerical approach is presented to characterize the motion-dependent forces. The model was used to predict these forces in flexible fuel kernel. In addition, an analytical model was developed utilizing the force model to predict the dynamic response of the fuel bundle. The dynamic response was compared with the available experimental data. In the second part, a fully-flexible fuel bundle structural model was developed to investigate the dynamic response of the fuel bundle under various excitation mechanisms. The model is capable of predicting the vibration response of fuel bundles with a large number of elements and various end conditions, such as flexible endplates. The fuel bundle and the supporting structure were modelled utilizing finite beam and plate elements. The contacts between the system components were modelled using the single point contact method (SPC). Fluid excitations, such as turbulence, pressure pulsation, and motion-dependent forces, were included in the model. Finally, the irradiation effects on the mechanical behavior of the fuel bundle is investigated using the same structural model. This was accomplished by utilizing a constitutive model that describes the thermal and irradiation effects on the mechanical properties. The current work represents a major advancement step towards a realistic modelling of the complex dynamics of fuel bundles.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".