Adaptive sampling for interpolation of reduced-order aeroelastic systems
File(s)
Accepted version
Author(s)
Goizueta, Norberto
Wynn, Andrew
Palacios, Rafael
Type
Journal Article
Abstract
A new strategy for the interpolation of parametric reduced-order models of dynamic aeroelastic systems is introduced. Its aim is to accelerate the numerical exploration of geometrically nonlinear aeroelastic systems over large design spaces or multiple flight conditions. The parametric reduced-order models are obtained from high-dimensional models by Krylov-subspace projection. They are subsequently interpolated to acquire realizations inexpensively anywhere in the parameter space, where having the state space as opposed to interpolating an output metric permits the use of linear analysis tools. The interpolation scheme is heavily conditioned by the available training points; thus, a novel methodology based on adaptive sampling and a combinatorial use of the available true-systems knowledge is presented, whereby we reuse all known data of the true models as different combinations of training and testing data to build statistical surrogates of the interpolation error across the parameter space and refine the sampling in those regions that need it. This minimizes the number of costly to evaluate function calls and ensures that parameter space regions are sampled according to the underlying system dynamics. The initial implementation of this adaptive sampling strategy is demonstrated on a very flexible wing with a complex stability envelope.
Date Issued
2022-11-01
Date Acceptance
2022-06-29
Citation
AIAA Journal: devoted to aerospace research and development, 2022, 60 (11), pp.6183-6202
ISSN
0001-1452
Publisher
American Institute of Aeronautics and Astronautics
Start Page
6183
End Page
6202
Journal / Book Title
AIAA Journal: devoted to aerospace research and development
Volume
60
Issue
11
Copyright Statement
© 2022 by Norberto Goizueta, Andrew Wynn, and Rafael Palacios. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the eISSN 1533-385X to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp.
Sponsor
Engineering and Physical Sciences Research Council
Grant Number
2297076
Subjects
Science & Technology
Technology
Engineering, Aerospace
Engineering
INDUCED-DRAG CALCULATIONS
VORTEX-LATTICE METHOD
DYNAMICS
DESIGN
MODELS
REDUCTION
OPTIMIZATION
SIMULATION
Aerospace & Aeronautics
0901 Aerospace Engineering
0905 Civil Engineering
0913 Mechanical Engineering
Publication Status
Published
Date Publish Online
2022-07-29