Optimization of a ducted fan propulsion system for a single engine aircraft
Bibliographic record
Abstract
The objective of this study was to perform a 3D aerodynamic shape optimization on a ducted fan propulsion system configured for cruise flight on an aircraft. The initial shapes of the duct and hub were determined using a basic grid searching optimization approach. An efficient optimization algorithm was created that utilized the BFGS searching technique with a QuasiNewton line search to refine the initial geometry. The ducted fan was chosen to be controlled by 13 control points connected using a combination of splines, ellipses and conics. The optimum design resulted in a 33.54% and 36.45% reduction in drag for the duct and hub respectively. The propeller thrust was also increased by 141.49%. The optimization methodology used throughout this study proved to be an efficient technique in finding the optimal design to within a high degree of resolution based on the entire design space considered.
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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".