期刊
AERONAUTICAL JOURNAL
卷 120, 期 1226, 页码 601-626出版社
CAMBRIDGE UNIV PRESS
DOI: 10.1017/aer.2016.12
关键词
aeroelasticity; reduced order modeling; surrogate modeling; neural networks; proper orthogonal decomposition; HIRENASD
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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