2,433 research outputs found
Magnetic eddy viscosity of mean shear flows in two-dimensional magnetohydrodynamics
Magnetic induction in magnetohydrodynamic fluids at magnetic Reynolds number
(Rm) less than~1 has long been known to cause magnetic drag. Here, we show that
when and the fluid is in a hydrodynamic-dominated regime in
which the magnetic energy is much smaller than the kinetic energy, induction
due to a mean shear flow leads to a magnetic eddy viscosity. The magnetic
viscosity is derived from simple physical arguments, where a coherent response
due to shear flow builds up in the magnetic field until decorrelated by
turbulent motion. The dynamic viscosity coefficient is approximately
, the poloidal magnetic energy density
multiplied by the correlation time. We confirm the magnetic eddy viscosity
through numerical simulations of two-dimensional incompressible
magnetohydrodynamics. We also consider the three-dimensional case, and in
cylindrical or spherical geometry, theoretical considerations similarly point
to a nonzero viscosity whenever there is differential rotation. Hence, these
results serve as a dynamical generalization of Ferraro's law of isorotation.
The magnetic eddy viscosity leads to transport of angular momentum and may be
of importance to zonal flows in astrophysical domains such as the interior of
some gas giants.Comment: 16 pages, 8 figure
Bringing global gyrokinetic turbulence simulations to the transport timescale using a multiscale approach
The vast separation dividing the characteristic times of energy confinement
and turbulence in the core of toroidal plasmas makes first-principles
prediction on long timescales extremely challenging. Here we report the
demonstration of a multiple-timescale method that enables coupling global
gyrokinetic simulations with a transport solver to calculate the evolution of
the self-consistent temperature profile. This method, which exhibits resiliency
to the intrinsic fluctuations arising in turbulence simulations, holds
potential for integrating nonlocal gyrokinetic turbulence simulations into
predictive, whole-device models.Comment: 7 pages, 3 figure
Investigation of a Multiple-Timescale Turbulence-Transport Coupling Method in the Presence of Random Fluctuations
One route to improved predictive modeling of magnetically confined fusion
reactors is to couple transport solvers with direct numerical simulations (DNS)
of turbulence, rather than with surrogate models. An additional challenge
presented by coupling directly with DNS is that the inherent fluctuations in
the turbulence, which limit the convergence achievable in the transport solver.
In this article, we investigate the performance of one numerical coupling
method in the presence of turbulent fluctuations. To test a particular
numerical coupling method for the transport solver, we use an
autoregressive-moving-average model to efficiently generate stochastic
fluctuations with statistical properties resembling those of a gyrokinetic
simulation. These fluctuations are then added to a simple, solvable problem,
and we examine the behavior of the coupling method. We find that monitoring the
residual as a proxy for the error can be misleading. From a pragmatic point of
view, this study aids us in the full problem of transport coupled to DNS by
predicting the amount of averaging required to reduce the fluctuation error and
obtain a specific level of accuracy.Comment: 18 pages, 9 figure
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