euratom – medc association days magurele, 26-27 november, 2009 trapping, transport &...
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EURATOM – MEdC Association Days
Magurele, 26-27 November, 2009
Trapping, transport
&
turbulence evolution
Madalina Vlad
Plasma Theory Group
National Institute of Laser, Plasmas and Radiation Physics,
Typical trajectory in the plane perpendicular to the magnetic field generated by the ExB stochastic drift in turbulent plasmas
Random sequence of trapping events and long jumps(completely different of the trajectories in Gaussian stochastic processes)
We have developed in the last decade semi-analytical methods, which are able to determine the statistics of such trajectories
Trapping completely changes trajectory statistics:
• memory effects (long tailes of the correlation of the Lagrangian velocity)
• anomalous transport regimes (diffusion coefficients with different dependence on the parameters, even opposite)
• non-Gaussian distribution of displacements
• high degree of coherence
• trajectory structures
What is the influence of trajectory trapping on the evolution of turbulence ??
Content
1) Test particle statistics in stochastic potential A short review of 10 year work
2) Test modes in turbulent plasmaA more detailed presentation of some results that could trap us for the next 10 years
1) Test particle statistics in stochastic potential We consider a turbulent plasma with given (measured) statistical characteristics of the stochastic potential and study test particle motion
Non-linear stochastic equation:
where is a stationary and homogeneous stochastic velocity field with Gaussian
distribution and known spectrum or Eulerian correlation (EC):
,0)0(),),(()(
xttxvdt
txd
),( txv
,,),(),(),( 21111
cc
txfttxxtxtxE
where is the amplitude , the correlation length, the correlation time.cc
c
cfl
fl
c
c
c VV
VK
,,The Kubo number :
(describes the decorrelation due to time variation of the stochastic field).
B
etxv z
),(
To determine: The statistical properties of the trajectories: the probability of displacements (pdf) P(x,t)
c
cxD
dt
txdtD
dxxtxPtx
)(
,)(
2
1)(
,),()(
22
22
)),(()0,0()( ttxvvtL jiij
,')'()(0t
xx dttLtD ,')'('2)(0
2 t
xx dttLtttx
Lagrangian velocity correlation (LVC) :
Note: -Test particle diffusion coefficients are the same with those obtained from the correlation of velocity and density fluctuation if there is space-time scale separation between fluctuations and the main gradients (due to the zero divergence of the ExB drift);- The characteristics of the turbulence and all the other components of the motion are input data
(A) The invariance of the potential for the static case
(Hamiltonian equation of motion)
• static case ( ): invariance of the potential and permanent trapping on the contour lines;
• slowly varying potential (K > 1): approx. invariance of the potential and temporary trapping
• potential with fast time variation (K < 1): no trapping.
t
ttx
t
ttx
x
ttxttxv
dt
ttxd
ii
)),(()),(()),(()),((
)),((
K
(B) The statistical invariance of the Lagrangian velocity due to
for stationary and homogeneous turbulence.
0),( txv
),()0),0(()),(( txvPxvPttxvP
There are two strong constraints for the statistical methods:
Semi-analytical statistical methods
The existing analytical methods are not compatible with the conditions (A) and (B). They do not describe trajectory trapping
The decorrelation trajectory method (DTM) 1998
(M.Vlad, F. Spineanu, J. H. Misguich, R. Balescu, “Diffusion with intrinsic trapping in 2-d incompressible stochastic velocity fields”, Physical Review E 58 (1998) 7359)
- DTM is based on a set of simple (deterministic) trajectories determined from the Eulerian correlation EC of the stochastic potential. - main consequences of condition (A) are fulfilled, condition (B) is not; - Main physical result: trapping produces memory effects (long-time correlation of the Lagrangian velocity), subdiffusive transport for static potential, and anomalous diffusion regimes.
The nested subensemble method (NSM) 2004
(M. Vlad, F. Spineanu, “Trajectory structures and transport”, Physical Review E 70 (2004) 056304(14))
- NSM is a systematic expansion based on dividing the space of realizations of the stochastic potential in nested subensembles. NSM yields detailed statistical information.- all consequences of (A) are fulfilled, condition (B) is improved (but not enough in order 2)
- Main physical result: trapping determines coherence in the stochastic motion and quasi-coherent trajectory structures.
The velocity on structure method (VS) 2009
- Both conditions (A) and (B) are respected; - Trajectory structures and the memory effects are confirmed and better described - Main physical result: trapping in a moving potential generates flows.
The probability of displacements for static potential
Time invariant part formed by trajectory structures of different scales (vortical motion)
Moving maximumof trajectories that are not in a structure at that time (radial motion).Decreasing number of free particles.
Note: this gives the probability of one-step jumps (fractal diffusion)
dxxtxPxPtxtFDt
txtD ftrB
22
2
)],()([)(),()(
)(
The diffusion coefficient for static potential:
constant at large t
22)( tVtn f
Decay of D(t) due to trapping
Correlation of the Lagrangian velocity with long negative tail that exactly compensates the positive part at small time delay
Subdiffusive transport (and memory !)
Effect of a perturbation = decorrelation mechanism characterized by a time d2V
t
fl
* The LVC is not influenced; Transport coefficient independent onand stable to such perturbations.
dfld
* The negative part of the LVC is cut out;
Anomalous diffusion regime (increased diffusion at stronger decorrelation)
Trajectory trapping No trajectory trapping
• Weak decorrelation mechanism with large decorrelation time
dwhenD
fl
• Strong decorrelation mechanism with small decorrelation timefld
dd VDwhenD 2,
The effect of time variation of the potential (finite K):
Decay of D due to trapping.
The effect of parallel motion: the correlation of the potential decays because particles move out of the correlated zone along the magnetic field.
Effective Kubo number:II
IIfl
fl
IIII
II
IIeff v
KKK
KKK
,,
11 effII KK
The effect of collisions: diffusion of the potential correlation. E(x) is not destroyed but spreaded due to collisional motion.
Effective Kubo number:
02/3 ,
21
D
K
KKeff
No trapping for electrons
BDKFDKD BB
),()(
Effect of an average velocity: V
VV d
d
1dVTrapping exists for and determines “the acceleration” of the free particles (on the opened contour lines), which reach an average velocity
• nonlinear process related to the statistical invariance of the Lagrangian velocity;• not a dynamical effect but determined by the selection of the free particles.
df VV
Trapping effects for fast particles;
Pinch induced by the gradient of the magnetic field;
.....
Always rather surprising nonlinear effects were found in the presence of trapping
The general conclusion of all this studies of test particles stochastic fields:
Trapping determines: memory effects,
anomalous transport,non-Gaussian distribution,
high degree of coherence (trajectory structures).
Trapping exists when K > 1 and if the other components of the motion are weak perturbations (collisions, average flow, …)
...,1/,1/0 VVVD dc
•M. Vlad, F. Spineanu, J.H. Misguich, R. Balescu, “Diffusion with intrinsic trapping in 2-d incompressible velocity fields”, •Physical Review E 58 (1998) 7359-7368;•M. Vlad, F. Spineanu, J.H. Misguich, R. Balescu, “Collisional effects on diffusion scaling laws in electrostatic turbulence”, Physical Review E 61 (2000) 3023-3032•M. Vlad, F. Spineanu, J.H. Misguich, R. Balescu, “Diffusion in biased turbulence”, Physical Review E 63 (2001) 066304•M. Vlad, F. Spineanu, J.H. Misguich, R. Balescu, “Electrostatic turbulence with finite parallel correlation length and radial diffusion”, Nuclear Fusion 42 (2002), 157-164.•M. Vlad, F. Spineanu, J.H. Misguich, R. Balescu, “Reply to ‘Comment on Diffusion in biased turbulence’”, Physical Review E 66 (2002) 038302.•M. Vlad, F. Spineanu, J.H. Misguich, R. Balescu, “Magnetic line trapping and effective transport in stochastic magnetic fields”, Physical Review E 67 (2003) 026406, 1-12.•M. Vlad, F. Spineanu, “Trajectory structures and anomalous transport”, Physica Scripta T107 (2004) 204-208.•M. Vlad, F. Spineanu, “Trajectory structures and transport”, Physical Review E 70 (2004) 056304(14).•M.Vlad, F. Spineanu, J. H. Misguich, J.-D. Reusse, R. Balescu, K. Itoh, S. –I. Itoh, “Lagrangian versus Eulerian correlations and transport scaling”, Plasma Physics and Controlled Fusion 46 (2004) 1051-1063.•M. Vlad, F. Spineanu, “Larmor radius effects on impurity transport in turbulent plasmas”, Plasma Physics and Controlled Fusion 47 (2005) 281-294.•M. Vlad, F. Spineanu, S.-I. Itoh, M. Yagi, K. Itoh , “Turbulent transport of the ions with large Larmor radii”, Plasma Physics and Controlled Fusion 47 (2005) 1015-1029.•M. Vlad, F. Spineanu, S. Benkadda, “Impurity pinch from a ratchet process”, Physical Reviews Letters 96 (2006) 085001.•M. Vlad, F. Spineanu, S. Benkadda, “Collision and plasma rotation effects on ratchet pinch”, Physics of Plasmas 15 (2008) 032306 (9pp).•M. Vlad, F. Spineanu, S. Benkadda, “Turbulent pinch in non-homogeneous confining magnetic field”, Plasma Physics Controlled Fusion 50 (2008) 065007 (12pp).•M. Vlad, F. Spineanu, “Vortical structures of trajectories and transport of tracers advected by turbulent fluids”, Geophysical and Astrophysical Fluids Dynamics 103 (April 2009) 143-161.
Balescu R., Aspects of Anomalous Transport in Plasmas, Institute of Physics Publishing (IoP), Bristol and Philadelphia, 2005.
Many other applications :
Petrisor I., Negrea M., Weyssow B., Physica Scripta 75 (2007) 1.Negrea M., Petrisor I., Balescu R., Physical Review E 70 (2004) 046409.
Balescu R., Physical Review E 68 (2003) 046409.Balescu R., Petrisor I., Negrea M., Plasma Phys. Control. Fusion 47 (2005) 2145.
still much many to be done (fluids, astrophysics,…)
Other people begin to work with DCT method
M. Neuer, K. Spatschek, Phys. Rev. E 74 (2006) 036401 T. Hauff, F. Jenko, Physics of Plasmas 13 (2006) 102309
• We consider a turbulent plasma with given (measured) statistical characteristics of the stochastic potential and study linear test modes
• AIM: to find the effect of trajectory trapping on test modes
The growth rate and frequency of the test modes are determined as function of the statistical characteristics of the background turbulence
2) Test modes in turbulent plasma
The drift (universal) instability in cartezian slab geometry, with constant magnetic field and density gradient. Turbulence is developed, with inverse cascade and vortical structures.
x
• Drift instability in cartezian slab geometry, with constant magnetic field and density gradient in collisionless plasmas.
-The limit of zero Larmor radius of the ions: - stable drift waves - potentials that move with the diamagnetic velocity
z
x
yB
dn0/dx
- The instability is produced by the combined effect of the non-adiabatic response of the electrons and of the finite Larmor radius (FLR) of the ions
0
0**
0
***2
*
2
2
)(
VV
VVVk
vk
Vk
eff
effeffy
Tez
effy
,2
22
00
Lik
dx
dn
Ben
TV 0
0*
0,* Vk y
),(),,(),,( 0*0 zxztVxtzx is the initial condition ]
1,2/4
1
2 **0
2
max
kVVvk
k eff
Tez
y
The formal solution of the Vlasov equation for an initial perturbation with
obtained with the method of the characteristics (integration along trajectories):
),(0 zx
t
ze
yzMze tvzxVdvFdv
T
e
T
tzxexntzxn
0
*0 ),(),()(),,(
1)(),,(
,),(,),(
,),()()(
),,(1)(),,(
0
*2
0
0
zxzxB
zxVdvFvdT
exn
T
tzxexntzxn
tijij
t
yM
i
),,(),,( tzxntzxn ie ),,( tzx
The average propagator and the average effect of the diamagnetic velocity fluctuations are determines using trajectory statistics
zzxtzxzxtx
vd
dz
B
etVx
d
xdz
zd
,;,,;
,)(
0
The background turbulence produces the stochastic ExB drift in the trajectories (characteristics)
))(exp()(exp tixxkid
t
Average over the trajectories
- the characteristic times ordering is used for simplifications: the parallel motion of the ions and the ExB drift for electrons are neglected
The existence of trapping is determined by the amplitude of the ExB drift: it appears when V is larger than the velocity of the potential
VVV dd /The trapping parameter for drift type turbulence is
iIIcfl
eII *
iIIcfl
eII *
QL (no trapping):
NL (trapping) :
• nonlinear effects appear in ion trajectories if • electron trajectories have quasiliniar statistics
VVd
,/4/ *2* VkVdc
dV
The ordering of the characteristic times is
Thus
Vkvk flezeII 2/2,/2
Effects of the background turbulence through the propagator
Turbulent plasma with small amplitude (quasilinear turbulence )
• the trajectories are Gaussian• the propagator is
0
2
0
***2
2
2
2
)(
ii
effeffy
Tez
DkVVVk
vk
The change appears only in the growth rate: damping due to ion diffusion
dVV
ii
f
Dik
ni 2
0
0**
*
2
VV
Vk
eff
effy
Damping of the test modes at large k (resonance broadening - Dupree)
The amplitude of the potential continues to grow and the correlation length is of the order of the Larmor radius
The probability of displacements is non-Gaussian
Time invariant part formed by trapped trajectories (vortical motion)
Moving maximumof trajectories that are not in a structure at that time(radial motion).Decreasing number of free particles.
Weak trapping ftrd nnVV ,
• The distribution of displacements is approximated by two Gaussian functions
(one for the trapped particles (with fixed width) and one of diffusive type)
is the size of the structures of trapped trajectories
• the propagator is
tDStxtxGxGtxP iiiftr 2)(),,()(),( 22
ii
iiDik
Ski 222 1)
2
1exp(
iS
)(
2
1exp *
22 VSk ii Effect of ion trajectory structures
0
0**
0
2
0
***2
*
2
2
2
2
)(,
VV
DkVVVk
vkVk
eff
ii
effeffy
Tez
effy
Decrease of the effective diamagnetic velocity
Displacement of the unstable range toward small k due to trajectory structures, decrease of the maximum growth rate and of spectrum width
The amplitude of the turbulence and its correlation length increase.The inverse cascade appears as the shift of the unstable wave numbers
The moving stochastic potential determines ion flows Trapped particles move with and free particles move in opposite direction 0)( tx
)(2 tx
dV
0
dV 'V
f
tr
ftr
n
nVV
tVntVntx
*
*
'
0')(
is large and
has ballistic time-dependence (because of this separation)
Strong trapping ftrd nnVV ,
Generation of ion (zonal) flows in opposite directions with zero total flux
• The distribution of displacements is approximated by two Gaussian functions
• the propagator is
),',(),(),( tVyxGntVyxGntxP ffdtr
iiy
f
y
trii
DikVk
n
Vk
nSki 2
*
2
')exp(
ftr
eff
trii
effeffy
Tez
effy
nnn
nnVV
nDk
nVVVVk
vk
Vk
/
2
2)1(
2
2
2
))((
0
0**
0
02
0
****2
*
The ion flows modify both the growth rate and the effective diamagnetic velocity
The ion flows induced by the moving potential determines the increase of the effective diamagnetic velocity and the decrease of the growth rate
*0*0* 0,, nVVnV effeff
For n 1 the growth rate is negative for all k
The ion (zonal) flows determine the damping of drift modes
It increases with the increase of n, becomes larger than the diamagnetic velocity (first for small k) mode damping
Effects of the background turbulence through the fluctuations of the diamagnetic velocity
• they appear due to the coupling of the non-adiabatic response of the ions to the background potential through ion trajectories
• the fluctuations of the diamagnetic velocity determine a new term in the growth rate of the modes:
),()0,0(,'
)2()2(2
2
2
2
2
))((
'
00
*
0
02
0
****2
xvy
vMMddR
n
VRkk
nDk
nVVVVk
vk
jiijij
t
ij
ijjitr
ii
effeffy
Tez
• it is much more complicated and it was not possible to obtain a simple evaluation;•The component corresponds to modes with (zonal flow modes).11R 02 k
• quasilinear turbulence: all the components of the tensor are zero
• for weak trapping the non-diagonal component appear but only for non-isotropic turbulence;
• for strong trapping the anisotropy induced by particle flows with the moving potential leads to
Thus, zonal flow modes (with ) are generated due to ion flows. As n increases to 1, the asymmetry induced by the ion flows disappears and
The process does not appear as a competition between drift modes and zonal flow modes, but as the effect of the ion flows induced by the moving potential.
Note- These are simplified estimations that do not take into account the strongly non-isotropic
diffusion coefficients and the non-isotropy of the turbulence.
ftrd nnVV ,011 R
ftrd nnVV ,011 R
0,02 k
011 R
Conclusion Trapping determines a strong and complex influence on test modes in turbulent plasmas producing large scale potential cells and zonal flows.
Nonlinear evolution in which ion trapping determines strong changes in the turbulence that are eliminates later. Drift turbulence does not saturate but has a complex intermittent (oscillatory) behaviuor.- the trapped particles that form trajectory structures lead to long correlations lengths;- the potential motion combined with trapping stabilizes and damps the drift modes (first those with small k) and in the same time generates zonal flow modes (with ), which eventually are damped when the ion flows becomes symmetrical (n=1).
0,02 k
The nonlinear growth rate of the test modes on drift turbulence is
),()0,0(,'
)(2
1exp
2
2)1(
2
2
2
))((
'
22
0
0**
*0
02
0
****2
*
xvy
vMMddR
VSk
nnVV
VRkkn
DknVVVVk
vk
Vk
jiijij
t
ij
ii
eff
effijji
trii
effeffy
Tez
effy
),()0,0(,'
)(2
1exp
2
2)1(
2
2
2
))((
'
22
0
0**
*0
02
0
****2
*
xvy
vMMddR
VSk
nnVV
VRkkn
DknVVVVk
vk
Vk
jiijij
t
ij
ii
eff
effijji
trii
effeffy
Tez
effy
(1) Dupree turbulent damping (V>0)
(2) Trajectory structures 00* ;, ftr nnVV
(3) Ion flows ftr nnVV ,*
(3) Fluctuations of *V
Trajectory trapping determines several types of effects; some of them acts simultaneously, others at different stages of the evolution.