Bibliographic record
Abstract
Slot airflow measurements in a push-type telecom shelf revealed significant non-uniformity produced by the strongly swirling and highly directional annular exhaust flow from the three high hub-tip ratio, mixed-flow fans. Similar flows were measured with plenum heights of 30 mm and 58 mm above the fans. A shelf CFD model was created, complemented by testing and modeling of a single fan in a test rig. The fan geometry was modeled exactly, but without the blades and motor struts, and tangential/axial body forces were added to the appropriate momentum equations in the fan volume to reproduce the test rig swirl and pressure rise respectively. Exhaust velocities were also measured, one-half tip diameter from the fan discharge, providing the radius of peak exhaust velocity. This radius was then matched in the test rig CFD model by imposing a radial body force in the fan volume. The resulting calibrated body forces were then applied to the shelf model, improving agreement with experiment compared to the same fan model without the calibrated radial force. To facilitate such calibration, either by electronic cooling software vendors or users, fan manufacturers should provide measured exhaust swirl (most important) and radial spreading (less important) data as well as the usual pressure rise curves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".