Aerodynamic Investigation of Shrouded Rotors with Dual Exit Channels
Bibliographic record
Abstract
The escalating demand for rotary-wing aerial vehicles capable of achieving both high forward speeds and reliable hover performance has become imperative across various sectors. These vehicles can be broadly categorized based on whether their rotor(s) is (are) shrouded or not. Shrouded rotors enhance aerodynamic performance by improving thrust and eliminating blade-tip vortex/losses, among other factors. These aspects augment the effective diameter of the rotor and optimize airflow through the shroud. Consequently, a shrouded rotor produces a greater total thrust compared to an open rotor, under the same (ideal) power consumption. Furthermore, the induced velocity flow field of a shrouded rotor exhibits increased uniformity compared to an open rotor, attributed to the shroud's presence, which mitigates power losses. This paper presents a parametric computational investigation centered on the hypothesis, that dividing the shroud exit channel into convergent inner and divergent outer channels would enhance flow uniformity, reducing power losses, and preventing airflow separation from the main shroud's inner walls. The validity of this hypothesized concept is demonstrated through extensive computational fluid dynamic (CFD) simulations. The paper includes a case analysis utilizing experimental data from a highly-maneuverable drone, named Navig8, equipped with a 9-inch shrouded propeller where various shrouded configurations are examined using Computational Fluid Dynamics. Results typically show an increase in total thrust with the incorporation of an inner shroud for a given power.
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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 | 0.000 |
| 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) | 0.001 | 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".