Incorporation of Producibility Considerations into an Aircraft Multidisciplinary Design Optimization Framework
Bibliographic record
Abstract
In recent years, Multidisciplinary Design Optimization has become an increasingly important tool during the process of aircraft design. Lockheed Martin, under contract to the Air Force Research Laboratory, recently completed a program known as EXPEDITE (EXPanded Multidisciplinary Design Optimization (MDO) for Effectiveness Based DesIgn TEchnologies) that made advances across multiple aspects of MDO. This paper describes recent developments, focused on methods to account for producibility early in the aircraft design process. Producibility is a measure which has been frequently neglected in early conceptual design trades due to the difficulty in quantifying producibility concerns in an abstract way. This work demonstrates that it is possible to quantify the effect of various design features on potential producibility-related factors by introducing a producibility risk flagging module, thereby enabling more robust conceptual design MDO studies with reduced downstream development risk.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".