Bibliographic record
Abstract
In this dissertation a new modular design method for morphing wings is presented. First, a design method was created, applying modularity and recon gurability to a morphing wing system. With modularity being a requirement for the morphing wing system, a discretization method is developed to determine the discrete number of modules required to perform a desired morphing maneuver. Then, a specialized, modular, recon gurable variable geometry truss mechanism is proposed to facilitate morphing. The specialized modular wing truss is a recon gurable, limited mobility parallel mechanism, adapted to t within the volume of a wing. The mobility of the wing truss module is analyzed via a branch-based mobility and connectivity analysis that imposes kinematic requirements on the truss mechanism. The mobility and connectivity requirements are used to perform an enumeration analysis to isolate candidate module con gurations for morphing. Then, a parametric kinematic constraint system is developed and applied to the wing module and the kinematic performance of the module is evaluated. The kinematics are applied to a mechanical prototype of the wing module for validation purposes. Finally, the kinematics are used to evaluate the motion response of a wing skin system to lay the foundation for detailed design.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".