Aerodynamic Design Optimization of a Transonic Strut-Braced-Wing Regional Aircraft
Why this work is in the frame
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Bibliographic record
Abstract
The aerodynamic design and fuel burn performance of a Mach-0.78 strut-braced-wing regional jet is investigated through aerodynamic shape optimization based on the Reynolds-averaged Navier–Stokes equations. Conceptual-level multidisciplinary design optimization is first performed to size the strut-braced-wing aircraft for a design mission similar to the Embraer E190-E2, with a design range of 3100 nmi at a maximum capacity of 104 passengers, and a maximum payload of 30,200 lb. For direct performance comparisons, a conventional tube-and-wing regional jet is also sized and optimized based on the same reference aircraft. Gradient-based aerodynamic shape optimization is then performed on wing–body–tail models of each aircraft, with the objective of drag minimization at cruise over a 500 nmi nominal mission. Design variables include twist and section shape degrees of freedom, which are realized through a free-form and axial deformation geometry control system, whereas nonlinear constraints include constant lift, zero pitching moment, minimum wing volume, and minimum maximum thickness-to-chord ratios. Results indicate that the optimizer is capable of mitigating shock formation, boundary-layer separation, and other flow interference effects from each wing design, including those within the wing–strut junction of the strut-braced wing. With year 2020 technology levels, the strut-braced-wing regional jet offers a 12.9% improvement in cruise lift-to-drag ratio over an Embraer E190-E2-like conventional tube-and-wing aircraft, which translates to a 7.6% reduction in block fuel for the nominal mission.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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