Experimental Study of Axial Fan Performances Operating In Constrained Environment: Application of Axial and Combined Axial–Radial Blockage
Bibliographic record
Abstract
This paper aimed to develop an experimental procedure for axial fans characterisation operating in constrained fields.The influence of an obstacle located downstream of a fan is studied experimentally on standardised test bench of the suction box type under different specific angular speeds.The axial fan of forward sweep category operates in free field referred as baseline configuration and in fields constrained by two blocking configurations axial and combined axial-radial.The blockages are produced by a flat plate, perpendicular to the axis of rotation of the fan for axial blockage case and two other plates placed radially for combined axial-radial blockage case, modelling, for example, the obstruction of a car internal combustion engine block.The four sets of global performances (pressure rise, flow rate, mechanical power and static efficiency) evolving with the different obstacles are compared to highlight their similarities.Variations in pressure rise as a function of flow rate were observed as the obstacle was changed depending upon the operating regime of the fan weather is working on axial or radial pattern discharge.The characteristic curves seem to evolve with substantial gain compared to the free field case especially when the blockage matched the flow configuration in the fans' wake.
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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".