Aerodynamically Optimal Regional Aircraft Concepts: Conventional and Blended-Wing-Body Designs
Bibliographic record
Abstract
The blended wing-body represents a potential revolution in efficient aircraft design, yet little work has explored the applicability of this design concept to small aircraft such as those that serve regional routes. We thus explore the optimal aerodynamic shape of both a blended wing-body and conventional tube-and-wing regional aircraft through high-fidelity aerodynamic shape optimization. A Newton-Krylov solver for the Euler and ReynoldsAveraged Navier-Stokes (RANS) equations is coupled with a gradient based optimizer, where gradients are calculated via the discrete adjoint method. Both the conventional and blended wing-body regional jets are optimized for a 500nmi mission at Mach 0.8 with the objective of minimizing drag subject to a trim constraint. Both Euler and RANS-based optimization is performed, with the result of the Euler optimization forming the starting point for the RANS-based optimization. Several optimization problems are considered with variation of sections, twist and planform. Root bending moment is constrained as a surrogate for structural weight in cases with planform variations. The optimized blended wing-body presented here exhibits a lift-to-drag benefit of 30% over a conventional design similar to existing regional aircraft. Changes in planform that result in aerodynamically optimal conventional and blended wing-body designs give a 21% lift-to-drag advantage to the blended wing-body.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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 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".