Sparse identification of a predator-prey system from simulation data of a convection model
Author(s) -
Magnus Dam,
Morten Brøns,
J. Juul Rasmussen,
V. Naulin,
Jan S. Hesthaven
Publication year - 2017
Publication title -
physics of plasmas
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.75
H-Index - 160
eISSN - 1089-7674
pISSN - 1070-664X
DOI - 10.1063/1.4977057
Subject(s) - physics , bifurcation , convection , statistical physics , nonlinear system , dynamical systems theory , turbulence , mechanics , consistency (knowledge bases) , flow (mathematics) , boundary value problem , mathematics , computer science , artificial intelligence , quantum mechanics
The use of low-dimensional dynamical systems as reduced models for plasma dynamics is useful as solving an initial value problem requires much less computational resources than fluid simulations. We utilize a data-driven modeling approach to identify a reduced model from simulation data of a convection problem. A convection model with a pressure source centered at the inner boundary models the edge dynamics of a magnetically confined plasma. The convection problem undergoes a sequence of bifurcations as the strength of the pressure source increases. The time evolution of the energies of the pressure profile, the turbulent flow, and the zonal flow capture the fundamental dynamic behavior of the full system. By applying the sparse identification of nonlinear dynamics (SINDy) method, we identify a predator-prey type dynamical system that approximates the underlying dynamics of the three energy state variables. A bifurcation analysis of the system reveals consistency between the bifurcation structures, observ...
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