Journal
AERONAUTICAL JOURNAL
Volume 120, Issue 1226, Pages 601-626Publisher
CAMBRIDGE UNIV PRESS
DOI: 10.1017/aer.2016.12
Keywords
aeroelasticity; reduced order modeling; surrogate modeling; neural networks; proper orthogonal decomposition; HIRENASD
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In this paper, a surrogate model approach for non-linear aerodynamics is presented in order to reduce the computational effort of coupled aeroelastic analyses. The usability of the approach is demonstrated in static as well as transient aeroelastic analyses of the HIRENASD wing-fuselage configuration. Furthermore, it is shown that the surrogate model approach is able to cover variations of flow conditions at a fixed Mach and Reynolds number.
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