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- W3197188061 abstract "Multiple Jovian moon flybys are common and essential for orbital transfers in Jupiter system exploration missions. To improve the preliminary design accuracy and find low-cost transfer trajectories, the restricted three-body model is used to describe the motion during the flybys. However, the restricted three-body problem has no analytical solution and requires numerical integration for computation, which requires a long computational time for the design of complex Jupiter missions. Therefore, an artificial neural network (ANN)-based model is proposed to improve the computing efficiency. The dynamics of the Jovian-moon flybys are analyzed to facilitate the design of the ANNs. A computational efficient map between the states before and after a flyby is constructed by the ANNs. Numerical simulations verify that the trained ANN-based model can achieve high accuracy and fast computational speed." @default.
- W3197188061 created "2021-09-13" @default.
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- W3197188061 date "2022-04-01" @default.
- W3197188061 modified "2023-09-25" @default.
- W3197188061 title "Fast computation of the Jovian-moon three-body flyby map based on artificial neural networks" @default.
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- W3197188061 doi "https://doi.org/10.1016/j.actaastro.2021.08.054" @default.
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