Toward High-Fidelity Aerostructural Optimization Using a Coupled ADjoint Approach
Why this work is in the frame
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Bibliographic record
Abstract
The tools required to perform high-fidelity aerostructural optimization are developed. Given the highly coupled nature of the aerostructural problem, a multidisciplinary feasible (MDF) approach is used for the framework. This approach is facilitated by a lagged-coupled adjoint, implemented using the ADjoint technique to sensitivity analysis. The ADjoint technique allows for the generation of very accurate and efficient adjoint sensitivities. The lagged-coupled adjoint system, which is equivalent to using a block-Jacobi method on the full coupled adjoint system, is solved using a pair of linear solvers. The structural portion of the system is solved using FEAP’s linear solver, while the CFD portion of the system is solved using PETSc. To demonstrate the accuracy of the coupled ADjoint, the sensitivities computed using the lagged-coupled approach are verified against complex-step sensitivities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it