Aerostructural Optimization of Aircraft Structures Using Asymmetric Subspace Optimization
Why this work is in the frame
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Bibliographic record
Abstract
A novel approach to the aerostructural optimization of wing-box structures called asymmetric subspace optimization, is presented and compared to the traditional multidisciplinary feasible (MDF) approach. In the asymmetric subspace optimization approach, the analyst chooses local and global sets of design variables and constraints. The local constraints and variables form a local optimization problem that is solved at each global iteration. This requirement changes the sensitivities of the global objective and constraints and requires a post-optimality sensitivity method. The main idea of this approach is to change the path to the optimal solution, by requiring the solution satisfy certain constraints at every global iteration without modifying the solution itself. The aerostructural problem examined here involves a linear stress analysis while the aerodynamic analysis is performed using a vortex lattice method.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it