Particle-in-Cell Simulations of Electron Transport from Plasma Turbulence
Zhihong Lin, Gregory Rewoldt
University of California, Irvine
Development of a reliable predictive capability for plasma turbulence is crucial
for achieving ignition conditions in the next step fusion experiments such as the
International Thermonuclear Experimental Reactor (ITER). Massively parallel
particle-in-cell (PIC) simulation has proven to be a powerful tool for studying
turbulent transport in magnetized plasmas, which typically involves nonlinear
kinetic effects, widely disparate spatial-temporal scales, and complex geometry.
Excellent progress in understanding the nature of ion transport driven by
electrostatic turbulence has been enabled by previous SciDAC-funded research
together with coordinated efforts in simulation, theory, and experiment. Since
a similar degree of understanding of electron transport remains an outstanding
question, the priority in current SciDAC-funded fusion research activity has
now shifted to this area with focus on driving mechanisms associated with
smaller scale, electromagnetic turbulence. This is a much more formidable
simulation task due to the large ion-to-electron mass ratio. Recently, important
progress has been made on studying two forms of turbulence potentially responsible
for the electron transport in fusion plasmas. First, full device simulations of
small scale turbulence driven by the electron temperature gradient (ETG) mode
has been enabled by efficient numerical algorithms and effective utilization of
powerful massively parallel computers. These large scale simulations together
with the associated development of analytic nonlinear theory have led to
key physics insights on nonlocal spectral transfer and wave-particle interactions,
which underlie the mechanisms of mode saturation and electron transport. The
new global simulation results challenge the prevailing picture based on earlier
simulations of ETG instabilities carried out for local geometry. Secondly,
global simulations of electromagnetic turbulence have recently been enabled
by the development of a finite element elliptic solver for complex toroidal
geometry. In order to invert an extremely large sparse matrix, this solver
utilizes the state-of-the-art parallel library PETSc which has been accelerated
by an algebraic multigrid solver hypre as a pre-conditioner. This new capability
also enables analysis of interactions between small-scale kinetic modes and
large scale magnetohydrodynamic (MHD) modes, which are believed to be important
in burning plasma experiments in ITER. Timely progress on these important
investigations has been enabled in large measure by productive interdisciplinary
collaborations with applied math and computational scientists within the framework
of the fusion component of the SciDAC Program.
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