Fuel burn evaluation of a transonic strut-braced-wing regional aircraft through multipoint aerodynamic optimisation
Bibliographic record
Abstract
Abstract This paper presents a relative fuel burn evaluation of the transonic strut-braced-wing configuration for the regional aircraft class in comparison to an equivalent conventional tube-and-wing aircraft. This is accomplished through multipoint aerodynamic shape optimisation based on the Reynolds-averaged Navier-Stokes equations. Aircraft concepts are first developed through low-order multidisciplinary design optimisation based on the design missions and top-level aircraft requirements of the Embraer E190-E2. High-fidelity aerodynamic shape shape optimisation is then applied to wing–body–tail models of each aircraft, with the objective of minimising the weighted-average cruise drag over a five-point operating envelope that includes the nominal design point, design points at $\pm 10\%$ nominal $C_L$ at Mach 0.78, and two high-speed cruise points at Mach 0.81. Design variables include angle-of-attack, wing (and strut) twist and section shape degrees of freedom, and horizontal tail incidence, while nonlinear constraints include constant lift, zero pitching moment, minimum wing and strut volume, and minimum maximum thickness-to-chord ratios. Results show that the multipoint optimised strut-braced wing maintains similar features to those of the single-point optimum, and compromises on-design performance by only two drag counts to achieve up to 11.6% reductions in drag at the off-design conditions. Introducing low-order estimates for approximating full aircraft performance, results indicate that the multipoint optimised strut-braced-wing regional jet offers a 13.1% improvement in cruise lift-to-drag ratio and a 7.8% reduction in block fuel over a 500nmi nominal mission when compared to the similarly optimised Embraer E190-E2-like conventional tube-and-wing aircraft.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".