Numerical Prediction of the Streamwise Fluidelastic Instability
Bibliographic record
Abstract
Abstract Recent experimental investigations have shown that tube arrays can become unstable in the streamwise direction. This is contrary to the long-held notion that fluidelastic instability is only a concern in the direction transverse to the flow. The possibility of the streamwise fluidelastic instability (SFEI) as a potential threat to the integrity of tube bundles was confirmed by the recent failures of newly installed replacement steam generators. A number of investigations were conducted to uncover the nature of this mechanism. A theoretical framework was developed by Hassan and Weaver (2016, “Modeling of Streamwise and Transverse Fluidelastic Instability in Tube Arrays,” ASME J. Pressure Vessel Technol., 138(5), p. 051304) to model streamwise fluidelastic instability in a bundle of flexible tubes. The model utilized a simple time lag expression for the flow channel area perturbation. The current work aims at developing a numerical model to precisely predict the flow perturbation characteristics in a tube bundle due to streamwise tube motion. Flow simulations were carried out for single phase fluid flow in a parallel triangle tube bundle array with 1.2, 1.5, and 1.7 pitch to diameter ratios. The numerical model was validated against numerical and experimental results available in the fluidelastic instability literature. Simulations were carried out for a range of reduced flow velocities. The model results showed that the upstream flow perturbation magnitude and phase are different from those obtained downstream of the moving tube. The obtained flow perturbation characteristics were implemented in the Hassan and Weaver (2016, “Modeling of Streamwise and Transverse Fluidelastic Instability in Tube Arrays,” ASME J. Pressure Vessel Technol., 138(5), p. 051304) model and the streamwise FEI threshold was predicted.
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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 | 0.001 |
| 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) | 0.000 | 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".