Control of Airflow Noise From Diesel Engine Turbocharger
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Turbocharger is one of the main parts for high power and low fuel consumption. But due to high RPM of turbocharger causes noise problem. Flow in the turbocharger is very fast and unsteady so it's very hard to estimate the noise and to reduce. So, we conducted experiment in anechoic room using airflow bench which uses compressed air as the power source. Through experiment we can identify the noise component radiated from turbocharger. As we know, tonal noise is dominant component which is related to RPM and some other noise components are confirmed. To analyze noise source and mechanism in detail, we proceed to numerical analysis. First to see the flow in the turbocharger, computational fluid dynamics(CFD) method is used. Using CFD method, we can see the flow in turbocharger and get base data for acoustic analysis. Surface pressure data resulted from CFD method is used for acoustic analogy analysis and boundary element method(BEM). Using these methods, we could understand the mechanism of airborne noise and classify the noise sources.</div></div>
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".