Sensitivity Analysis of Entrance Design Parameters of a Backward-Inclined Centrifugal Fan Using DOE Method and CFD Calculations
Bibliographic record
Abstract
Centrifugal fans with an electric motor included in the hub are commonly used in HVAC (heating, ventilation, and air conditioning) systems. A design of experiments (DOE) has been performed to study the effect of the entrance conditions of a backward-inclined centrifugal fan on its efficiency. The parameters involved are the base radius of the motor hub, the radius of the fan entry section, the deceleration factor throughout the entry zone (from the entry of the fan to the entry of the blade), and the solidity factor. Numerical simulation coupled with the DOE has been used for the sensitivity analysis of the entrance parameters. Initially, a complete factorial plan (24) was performed to screen the most influent parameters and interactions. This has shown that the motor’s cap radius, as well as its interactions with other parameters, is not significant. A second DOE, using composite central design (CCD which has a second order of accuracy) has then been performed on the remaining parameters (radius of the fan entry section, deceleration factor, and the solidity factor). The effects of these parameters and their interactions on the fan efficiency are now presented. A linear regression with three parameters has been performed to establish the efficiency distribution map. The methodology employed is validated by comparing the predicted results from the DOE and those from the numerical simulation of the corresponding fan.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".