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Title: Numerical efficacy study of data assimilation for the 2D magnetohydrodynamic equations
We study the computational efficiency of several nudging data assimilation algorithms for the 2D magnetohydrodynamic equations, using varying amounts and types of data. We find that the algorithms work with much less resolution in the data than required by the rigorous estimates in [7]. We also test other abridged nudging algorithms to which the analytic techniques in [7] do not seem to apply. These latter tests indicate, in particular, that velocity data alone is sufficient for synchronization with a chaotic reference solution, while magnetic data alone is not. We demonstrate that a new nonlinear nudging algorithm, which is adaptive in both time and space, synchronizes at a super exponential rate. [7] A. Biswas, J. Hudson, A. Larios and Y. Pei, Continuous data assimilation for the 2D magnetohydrodynamic equations using one component of the velocity and magnetic fields, Asymptot. Anal., 108 (2018), 1-43.
Authors:
;
Award ID(s):
1818754
Publication Date:
NSF-PAR ID:
10146236
Journal Name:
Journal of computational dynamics
Volume:
6
Issue:
1
Page Range or eLocation-ID:
131-145
ISSN:
2158-2491
Sponsoring Org:
National Science Foundation
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