Design and wind tunnel testing of a new concept of wing \nmorphing camber system
Bibliographic record
Abstract
This thesis presents the design and manufacturing of a new morphing wing system realized at the Laboratory of Research in Active Controls, Avionics and AeroServoElasticity (LARCASE). This morphing wing system can morph the camber of the wing by modifying its trailing and leading edges. To allow this modification, slots were made in the ribs of the wing, which made them flexible according to the theory of compliant mechanism. The structural strength of the wing was studied with the Finite Element Analysis (FEA) module of Catia V5 software by considering a pressure distribution on the wing surface. The aerodynamic performance of the morphing system was analyzed with the Computational Fluid Dynamics (CFD) module in Ansys-Fluent. The functionality of the morphing system was verified by static tests in the workshop, then by dynamic tests using the LARCASE Price-Paidoussis subsonic wind tunnel. The results obtained from the wind tunnel tests have show that the morphing wing system made it possible to maintain control of the aircraft while reducing its drag. The morphing system made it possible to keep constant the mass of the wing, and it did not require excessive power consumption. Thus, the design for a wing deformation system presented in this thesis is a good option to allow the manufacturing of morphing wings for the aircraft to improve its aerodynamic performance. This design allowed us to reduce fuel consumption, increase the maximum flight time or increase the payload of the aircraft.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".