Noise Characterization and Reduction Techniques of Multiple Axial Fans Unit
Bibliographic record
Abstract
Experimental noise characterization is performed on a multiple axial fans unit that is used to force air in common house hold or industrial appliances for cooling purposes. The acoustic field generated by the fans unit is mapped at two different conditions; namely, the normal operating condition and the maximum possible rotational speed. It is found that the noise generated by the fan unit has a distinct whistling tone at a frequency that matches the blade passing frequency. The whistling tone may be amplified due to further fluid-sound interactions with the casing of the unit. Hence, several noise reduction techniques are investigated in order to reduce the noise generated from the fans unit, such as annular silencers and L-shaped silencers. Finally, an innovative compact reflective/absorptive silencer is designed and the measurements indicate that it can achieve a noise reduction of 6.3 dBA at normal operating conditions and 9.5 dBA at extreme operating conditions.
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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 | 0.000 |
| 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) | 0.000 | 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".