|
Descripción
|
|
|---|---|
| A preliminary version of a data driven reduced order model (ROM) for dynamical systems is presented in this Chapter. This ROM synergically and adaptively combines a black-box full model (FM) of the system and extrapolate conveniently using a recent extension of standard dynamic mode decomposition called higher order dynamic mode decom- position (HODMD). These two are applied in interspersed time inter- vals, called the FM-intervals and the HODMD-intervals, respectively. The data for the each HODMD-interval is obtained from the applica- tion of the FM in the previous FM-interval. The main question is when extrapolation from HODMD is no longer valid and switching to a new FM-interval is necessary. This is made attending to two criteria, ensuring that an estimate of the extrapolation error and a measure of consistency are both conveniently small. In this sense, the present method is similar to a previous method called POD on the Fly, which was not a purely data driven method. Instead, POD on the Fly was based on a Galerkin projection of the governing equations that thus should be known. The new method presented in this paper is illustrated with several transient dynamics for the complex Ginzburg-Landau equation that converges to either periodic or quasi-periodic attractors. The resulting CPU acceler- ations factors (compared to the full model) are quite large. | |
|
Internacional
|
Si |
|
DOI
|
10.1007/978-3-030-20055-8 _ 54 |
|
Edición del Libro
|
|
|
Editorial del Libro
|
|
|
ISBN
|
978-3-030-20054-1 |
|
Serie
|
Advances in Intelligent Systems and Computing |
|
Título del Libro
|
14th International Conference on soft Computing Models in Industrial and Environmental Applications (SOCO 2019) |
|
Desde página
|
567 |
|
Hasta página
|
576 |