Acoustic resonance excitation and source mapping in co-axial piping systems with different junction edge geometries
Bibliographic record
Abstract
In this study, the excitation of acoustic resonance in a coaxial piping system consisting of two opposite pipe branches is experimentally investigated. A lumped element model is used to determine the complex acoustic source, enabling the prediction of resonance excitation under specific flow conditions. The model is validated by assessing the susceptibility of two opposite side branches to acoustic resonance excitation. The predicted acoustic resonance parameters show good agreement with experimental observations in terms of the Strouhal numbers and normalized acoustic pressure amplitudes across a range of flow velocities. Additionally, the effects of rounding and chamfering the edges of the branching junction on resonance excitation are explored. Results indicate that rounded edges produce higher acoustic pressure amplitudes compared to chamfered and sharp edges, with a significant increase in Strouhal numbers at resonance. Furthermore, increasing the rounding radius raises both the onset flow velocity and the lock-in region. The influence of flow development and acoustic radiation losses on the excitation mechanism is also investigated. Findings show that side branches with fully developed flow and reduced acoustic radiation losses to the main pipe are more prone to acoustic resonance excitation and resonate at higher Strouhal numbers. However, the predicted acoustic amplitude reaches a maximum once the upstream distance allows for full flow development over the branching junction. • A lumped element model is used to develop source maps for predicting acoustic resonance in a coaxial piping system. • This technique effectively captures excitation parameters, including resonant Strouhal numbers and pressure amplitude. • Measurements of the self-excited response validate the model and provide valuable insights into the excitation mechanism. • The geometry of the junction edge has a significant impact on the acoustic resonance excitation mechanism.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".