Multipoint High-Fidelity Aerostructural Optimization of a Transport Aircraft Configuration
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.212 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
This paper presents multipoint high-fidelity aerostructural optimizations of a long-range wide-body transonic transport aircraft configuration. The aerostructural analysis employs Euler computational fluid dynamics with a 2-million-cell mesh and a structural finite-element model with 300,000 degrees of freedom. The coupled adjoint sensitivity method is used to efficiently compute gradients, enabling the use of gradient-based optimization with respect to hundreds of aerodynamic shape and structural sizing variables. The NASA Common Research Model is used as the baseline configuration, together with a wing box structure that was designed for this study. Two design optimization problems are solved: one where takeoff gross weight is minimized, and another where fuel burn is minimized. Each optimization uses a multipoint formulation with five cruise conditions and two maneuver conditions. Each of the optimization problems have 476 design variables, including wing planform, airfoil shape, and structural thickness variables. Optimized results are obtained within 36 h of wall time using 435 processors. The resulting optimal configurations are discussed and analyzed for the aerostructural tradeoffs resulting from each objective. The takeoff gross weight minimization results in a 4.2% reduction in takeoff gross weight with a 6.6% fuel burn reduction, whereas the fuel-burn optimization resulted in an 11.2% fuel burn reduction with no significant change in the takeoff gross weight.
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The record
- Venue
- Journal of Aircraft
- Topic
- Advanced Aircraft Design and Technologies
- Field
- Environmental Science
- Canadian institutions
- —
- Funders
- Government of OntarioCompute CanadaUniversity of TorontoNational Aeronautics and Space Administration
- Keywords
- TakeoffAirfoilReduction (mathematics)AerodynamicsShape optimizationFinite element methodEngineeringControl theory (sociology)SimulationComputer scienceMathematicsStructural engineeringAerospace engineeringGeometry
- Has abstract in OpenAlex
- yes