An ensemble-variational framework approximates gradients via perturbed control vectors to optimize steady forcing in 2D cavity flows across quasi-periodic to chaotic regimes.
Jameson, Aerodynamic design via control theory
6 Pith papers cite this work. Polarity classification is still indexing.
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Derives analytic adjoint potential and stream function for 2D subcritical full potential flows, linking them to compressible Euler adjoints and analyzing unknown functions encoding Kutta condition perturbations for lift.
Two frameworks for nonlinear equality constraints in gradient-enhanced local Bayesian optimization achieve deeper convergence with fewer function evaluations than previous constrained BO methods and SciPy/MATLAB quasi-Newton optimizers on unimodal problems with 2-30 variables.
A discrete adjoint GKS is developed and verified for efficient aerodynamic shape optimization in turbulent flows, achieving design goals in few cycles.
Turbulence model choice causes up to 250% differences in geometric sensitivities during airfoil shape identification from wake data, showing that closure consistency is required for reliable inverse results.
Systematic benchmarks on NACA0012, RAE2822, and ONERA M6 cases show derivative-free optimizers competitive with adjoint-based methods and stronger in higher dimensions.
citing papers explorer
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An Ensemble Variational approach for High-Dimensional Open-Loop Flow Control
An ensemble-variational framework approximates gradients via perturbed control vectors to optimize steady forcing in 2D cavity flows across quasi-periodic to chaotic regimes.
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Analytic Full Potential Adjoint Solution for Two-dimensional Subcritical Flows
Derives analytic adjoint potential and stream function for 2D subcritical full potential flows, linking them to compressible Euler adjoints and analyzing unknown functions encoding Kutta condition perturbations for lift.
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A Framework for Nonlinearly-Constrained Gradient-Enhanced Local Bayesian Optimization with Comparisons to Quasi-Newton Optimizers
Two frameworks for nonlinear equality constraints in gradient-enhanced local Bayesian optimization achieve deeper convergence with fewer function evaluations than previous constrained BO methods and SciPy/MATLAB quasi-Newton optimizers on unimodal problems with 2-30 variables.
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A Discrete Adjoint Gas-Kinetic Scheme for Aerodynamic Shape Optimization in Turbulent Continuum Flows
A discrete adjoint GKS is developed and verified for efficient aerodynamic shape optimization in turbulent flows, achieving design goals in few cycles.
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Effect of Turbulence-Closure Consistency on Airfoil Identification
Turbulence model choice causes up to 250% differences in geometric sensitivities during airfoil shape identification from wake data, showing that closure consistency is required for reliable inverse results.
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Derivative-free optimization is competitive for aerodynamic design optimization in moderate dimensions
Systematic benchmarks on NACA0012, RAE2822, and ONERA M6 cases show derivative-free optimizers competitive with adjoint-based methods and stronger in higher dimensions.