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Frank Jenko
Max-Planck-Institut für Plasmaphysik, GarchingUniversität Ulm
Dynamics and turbulent transport in plasmas and conducting fluidsEcole de Physique, Les Houches, 9 March 2011
Introduction togyrokinetics
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Before we start…
The focus will be on various more fundamental properties ofmicroturbulence in magnetized plasmas
Like my predecessors, I will attempt to do some impedancematching, keeping in mind the mixed audience
Please feel free to interrupt me if you have a question
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Why inventgyrokinetics?
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ITER is one of the most challenging scientific projects
Plasma turbulencedetermines its energy confinement time
ITER and plasma turbulence
www.iter.org
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Ab initio simulations are based on GK
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ExB drift velocity
(random walk/mixinglength estimates)
potential contourspotential contours==
streamlines of streamlines of ExBExB velocityvelocity
Typical heat and particle diffusivities are of the order of 1 m2/s.
Turbulent mixing in a tokamak
GradientsGradients→→ fluctuationsfluctuations
→→ transporttransport
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Note: Usefulness of gyrokinetics for space and astrophysics
Some issues under investigation:
• Role of microturbulence in space physics?• transport across boundary layers• fast magnetic reconnection• coronal and solar wind heating
• How does MHD turbulence dissipate energy?
• How do fast particles interact with turbulence?
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Gyrokinetic theory:A brief guided tour
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Vlasov-Maxwell equations
Removing the fast gyromotionleads to a dramatic speed-up
Charged rings as quasiparticles;gyrocenter coordinates; keep kinetic effects
Dilute and/or hot plasmas are almost collisionless.
Thus, if kinetic effects (finite Larmor radius, Landau damping,magnetic trapping etc.) play a role, MHD is not applicable,
and one has to use a kinetic description!
What is gyrokinetic theory?
Details may be found in: Brizard & Hahm, Rev. Mod. Phys. 79, 421 (2007)
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The gyrokinetic ordering
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A brief historical reviewA. Bottino
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A Lagrangian approach
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Guiding center coordinates
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Guiding center coordinates (cont’d)
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Guiding center coordinates (cont’d)
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Including fluctuating fields
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Resulting Lagrangian 1-form
Eliminate explicit gyrophase dependence via near-identity (Lie) transformsto gyrocenter coordinates:
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Euler-Lagrange equations
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Gyroaveraged potentials
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Appropriate field equations
Nonlinear integro-differential equations in 5 dimensions...
Reformulate Maxwell’s equations in gyrocenter coordinates:
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Major theoretical speedups
Nonlinear gyrokinetic equations eliminate plasma frequency: ωpe/Ωi ~ mi/me x103
eliminate Debye length scale: (ρi/λDe)3 ~ (mi/me)3/2 x105
average over fast ion gyration: Ωi/ω ~ 1/ρ* x103
Field-aligned coordinates adapt to elongated structure of turbulent eddies: ∆||/∆⊥ ~ 1/ρ* x103
Reduced simulation volume reduce toroidal mode numbers (i.e., 1/15 of toroidal direction) x15 Lr ~ a/6 ~ 160 ρ ~ 10 correlation lengths x6
Total speedup x1016
For comparison: Massively parallel computers (1984-2009) x107
relative to original Vlasov/pre-Maxwell system on a naïve grid, for ITER 1/ρ* = a/ρ ~ 1000
G.Hammett
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Status quo in gyrokinetic simulation
over the last decade or so, GK has emerged as the standard approach to plasma turbulence
a variety of nonlinear GK codes is being used and (further) developed
these codes differ with respect to their numerics, physics, parallel scalability, and public availability
GYRO GTCGEM GS2
...
GENEORB5GYSELAELMFIRE
...
GKVG5D
...
US
Europe Japan
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• GENE is physically comprehensive (local and global) CFD code with applications to both tokamaks & stellarators (as well as astrophysics)
• two main goals: deeper understanding of fundamental physics issues and direct comparisons with experiments (interfaces to MHD codes)
• the differential operators are discretized via a combination of spectral, finite difference, finite element, and finite volume methods; the time stepping is done via a (non-standard) explicit Runge-Kutta method
• GENE is developed cooperatively by an international team, and it is publicly available (http://gene.rzg.mpg.de)
• GENE is very efficient computationally: parallelization over all phase space coordinates; code automatically adapts to hardware & chosen grid
Example: The simulation code GENE
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Massive parallelism
Strong scaling (fixed problem size) of GENE on Jülich’s JUGENE system
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Plasma microturbulence:Linear drive
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Perpendicular dynamics: de-/stabilization in out-/inboard regions
stable
unstable Rayleigh-Taylor instabilityAnalogy in a plasma:
Parallel dynamics: localization in outboard regions
Gradient-driven microinstabilities
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Trapped Electron Modes(TEMs)
Electron Temperature Gradient (ETG) Modes
Ion Temperature Gradient (ITG) Modes
Different kinds of microinstabilities drive different kinds of plasma turbulence
Drive (= transport)range dynamics isnot universal.
Plasma turbulenceis actually a multi-scale problem.
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Exceptional points
In the context of fusion energy,gaining a better understandingof plasma turbulence is crucial
Different microinstabilites (usuallyconsidered as separated) can betransformed into each other viacontinuous parameter changes.
The non-Hermiticity of thelinear gyrokinetic operatorleads to Exceptional Points.
Here, both eigenvalues andeigenvectors are identical.
Similar: Quantum physics, MHD[Stefani & Gerbeth, PRL 05] etc.
Kammerer, Merz & Jenko 2008
Riemann surface of f(z)=sqrt(z)
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In the context of fusion energy,gaining a better understandingof plasma turbulence is crucial
Exceptional points (cont’d)
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Plasma microturbulence:Nonlinear saturation?
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gene.rzg.mpg.de
Saturation of ITG modes: Zonal flows
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Secondary instabilities & ZF generation
Strintzi & Jenko 2007Xanthopoulos et al. PRL 2007
• Large-amplitude streamers are Kelvin-Helmholtz unstableThis secondary instability contains a zonal-flow component
• Near-equivalence to 4-mode approach
Simpletokamak
W7-Xstellarator
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Trapped electron mode turbulence
Pure TEM turbulence simulations [Dannert & Jenko, PoP 2005]:
- In the drive range, nonlinear and linear frequencies are identical
- In the drive range, there is no significant shift of cross phases w.r.t. linear ones
– No dependence of transport level on presence or absence of zonal flows
Zonal flows suppressed
linear
nonlinear
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ZF / Non-ZF regimes
Ernst et al., PoP 2009
ExB shearing rates exceed thegrowth rate only for ηe < 1
For mainly temperature gradientdriven TEM turbulence, ZFs(and GAMs) are relatively weak
Thus, in a wide region of parameterspace, the standard drift-wave / ZFparadigm does not hold
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Both weak and strong turbulence theories suggest that the ExB nonlinearity can be represented by a coherent part and a random noise part
and are fluctuating quantities; minimizing the model error , we obtain
Theory-motivated statistical analysis
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Low-ky drive range: large transport contributions, but small random noise; here, one finds:
Saturation of TEMs: “eddy damping”
~ky2
Merz & Jenko, PRL 2008
This is in line with various theories, including Resonance Broadening Theory (Dupree), MSR formalism (Krommes), Dressed Test Mode Approach (Itoh).
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Implications for transport modeling
NL frequency spectra
Results motivate use of thefollowing quasilinear model: GENE sim’s
QL model
In situations where ITG modesand TEMs compete, they cancoexist, and there can be non-trivial nonlinear interactions
Merz & Jenko, NF 2010
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Dissipation & cascadesin plasma turbulence
D.R. Hatch, P.W. Terry, W.M. Nevins, F. Merz & FJ
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Turbulence in fluids and plasmas –Three basic scenarios
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Saturation via damped eigenmodes
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Excitation of damped eigenmodes
Using GENE as a linear eigenvalue solver to analyzenonlinear ITG runs via projection methods, one finds…
unstableeigenmode
least damped eigenmode
ky=0.3drive range
strongly dampedeigenmodes
(fine-scale structurein v and z)
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Energetics
Turbulent free energy consists of two parts:
Drive and damping terms:
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Energetics in wavenumber space
Damped eigenmodes are responsible forsignificant dissipation in the drive range.
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Some energy escapes to high k
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Resulting spectrum decays exponentially @lo k, asymptotes to power law @hi k
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Multiscale wavenumber spectra
Poloidal wavenumber spectraof density fluctuations for pureTEM / ITG / ETG turbulence
Poloidal wavenumber spectraof density fluctuations for mixed
TEM / ITG – ETG turbulence
NL (!) ETG drive
L ETG drive
Universality? T. Görler & FJ, PoP 15, 102508 (2008)
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Gyrokinetics inspace and astrophysics
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Various multiscale challenges in space and astrophysics
Many phenomena involve fluid, ion, electron scales, e.g.:
• magnetic reconnection• shock waves• turbulence• cross-field transport
Simulations are challenged to address these issues.
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Current numerical approaches
MHD (including multi-fluid extensions)…the workhorse…
Kinetic (PIC or Vlasov, including δf versions)…the microphysics laboratory…
Bridging spatio-temporal scales:• large-scale kinetics (test particle approach)• hybrid codes (e.g. kinetic ions & fluid electrons)
Another option: Gyrokinetics…
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Solar wind turbulence: Dissipation?
Sahraoui et al., PRL 2009
Collisionless damping of(shear) Alfvén waves
Dannert & Jenko, CPC 2004
High-k MHD turbulence satisfies the gyrokinetic ordering!
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High-k Alfvén wave turbulence:Observations versus simulations
AW turbulence in the solar windBale et al., PRL 2005
GK simulation of AW turbulenceHowes et al., PRL 2008
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Broad-line regions in AGNs
Measured electromagnetic spectrafrom AGNs suggest the existence of…
…cold, dense clouds in a hot, dilute,magnetized medium in the centralregion of AGNs.
How can those cold clouds survive?
Standard model (e.g. Kuncic et al., MNRAS 1996):
Cold clouds are magnetically confined and formfilaments; perpendicular transport is negligible.
Gyrokinetic turbulence sets lower limit on cloud size!Pueschel et al.
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Summary and outlook
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Continuous advances concerning our under-standing of fundamental issues in plasmaturbulence; various links to HD and MHD(see also the talks by H. Doerk, A. Banon Navarro, and P. Morel)
Implications for plasma astrophysics andimportant practical consequences concerningthe efficient transport modeling of ITER plasmas
Magnetically confined plasmasin laboratory experiments or in nature