Aerodynamic Modelling of Unmanned Aerial System through Nonlinear Vortex Lattice Method, Computational Fluid Dynamics and Experimental Validation - Application to the UAS-S45 Bàlaam: Part 1.
Bibliographic record
Abstract
This paper describes a methodology to predict the aerodynamic behaviour of an Unmanned Aerial System. Aircraft design and flight dynamics modelling are mainly concerned with aerodynamics, and thus its estimation requires a high level of accuracy. The work presented here shows a new non-linear formulation of the classical Vortex Lattice Method and a comparison between this methodology and an experimental analysis. The new non-linear Vortex Lattice Method was performed by calculating the viscous forces from the strip theory, and the forces generated by the vortex rings from the vortex lifting law. The experimental analysis was performed on a reduced scale wing in a low speed wind tunnel. The obtained results were also compared to those obtained from semi-empirical methods programmed using DATCOM and our Fderivatives new in-house codes. The results have indicated the accuracy of the new formulation and showed that an aerodynamic model obtained with the aerodynamic coefficients predicted with this method could be useful for flight dynamics estimation.
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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".