Feasibility Study for Multi-Branches and Elbow in Stub Pipe System due to Flow-Induced Vibration Using Computational Fluid Dynamics
Bibliographic record
Abstract
Abstract Acoustic-induced vibration in piping system and other devices leads to premature wear and failure. Especially, in nuclear power plants, very high velocity and temperature gas flows inside pipe systems. Moreover, if a frequency due to the vibration in the piping system is overlapped with a natural frequency of the stud pipe, the magnitude of the amplitude will be increased resulting in severe failure. For example, damage can be considered as flow-induced acoustic resonance at the branch pipes of the safety relief valve in the main steam lines. Specially, the pipe system not only has multi-branches but also includes the elbow that the resonance could occurs making pressure oscillation stronger than that of a single branch because of the interaction between the branches and the elbow. This study has investigated a Computational Fluid Dynamics (CFD) analysis methodology to predict and quantify the vortex shedding frequencies and the pressure pulsation magnitude in the dead-end pipe. The influence of the pressure fluctuation amplitude between each branch, number of branch, and elbow is also investigated.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".