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, observed for the simulation data, and the identified underlying system.
Sparse identification of a predator-prey system from simulation data of a convection model
Magnus Dam, Morten Brøns, Jens Juul Rasmussen, Volker Naulin, Jan S. Hesthaven; Sparse identification of a predator-prey system from simulation data of a convection model. Phys. Plasmas 1 February 2017; 24 (2): 022310. https://doi.org/10.1063/1.4977057
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