Laminar Simulation of Flow Pulsations in Simplified Subchannel Geometries
Bibliographic record
Abstract
Flow pulsations in subchannel geometries play an important role in homogenization of fluid temperatures within a fuel rod bundle cross-section. As such, there is a strong need to develop accurate integral models that incorporate the underlying physics of these flows for inclusion in the broader safety analysis codes. This research is concerned with using computational fluid dynamics to investigate the flow pulsations in order to develop an enhanced understanding of the flow physics. The vast majority of previous experimental work has been in the turbulent regime, with varying degrees of geometric complexity. Previous numerical work has focused on steady or unsteady simulation of the turbulent experimental results, with the requirement that an appropriate turbulence model must be selected. Recent experimental work by Gosset and Tavoularis in 2006 has indicated that flow pulsations can occur under laminar conditions. Computational modeling of laminar flow pulsations provides an ideal framework for studying the physical mechanisms or instabilities that promote formation of the pulsations. Simulations of their experimental domain were run for a gap height normalized by the rod diameter (δ/D) of 0.3 and Reynolds numbers of 718, 900 and 955. These simulations found frequencies in the same range as Gosset and Tavoularis, as well as qualitatively similar particle tracks to their dye streaks. Analysis of the numerical pulsations showed them to be fluid rotations around the rod. These rotations were shown to be strongly correlated with the axial velocity gradient, which acted to transfer momentum from axial flow to the crossplane rotational pulsatile flow. The pulsations were shown to develop from a purely axial flow through disturbances in the axial velocity gradient, which initially arose near inflection points in the axial velocity profile in the spanwise direction. Under the influence of the axial velocity gradient and fluctuating pressure, these disturbances evolve into a sustained quasi-periodic flow.
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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 | 0.001 | 0.001 |
| 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) | 0.010 | 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".