A&A 482, 739-746 (2008)
DOI: 10.1051/0004-6361:200809365
A. Brandenburg1 - K.-H. Rädler2 - M. Schrinner3
1 -
NORDITA, Roslagstullsbacken 23, 10691 Stockholm, Sweden
2 -
Astrophysical Institute Potsdam, An der Sternwarte 16, 14482 Potsdam, Germany
3 -
Max-Planck-Institut für Sonnensystemforschung, 37191 Katlenburg-Lindau,
Germany
Received 8 January 2008 / Accepted 8 February 2008
Abstract
Aims. We determine the alpha effect and turbulent magnetic diffusivity for mean magnetic fields with profiles of different length scales from simulations of isotropic turbulence. We then relate these results to nonlocal formulations in which alpha and the turbulent magnetic diffusivity correspond to integral kernels.
Methods. We solve evolution equations for magnetic fields that give the response to imposed test fields. These test fields correspond to mean fields with various wavenumbers. Both an imposed fully helical steady flow consisting of a pattern of screw-like motions (Roberts flow) and time-dependent, statistically steady isotropic turbulence are considered. In the latter case the evolution equations are solved simultaneously with the momentum and continuity equations. The corresponding results for the electromotive force are used to calculate alpha and magnetic diffusivity tensors.
Results. For both, the Roberts flow under the second-order correlation approximation and the isotropic turbulence alpha and turbulent magnetic diffusivity are greatest on large scales and these values diminish toward smaller scales. In both cases, the alpha effect and turbulent diffusion kernels are approximated by exponentials, corresponding to Lorentzian profiles in Fourier space. For isotropic turbulence, the turbulent diffusion kernel is half as wide as the alpha effect kernel. For the Roberts flow beyond the second-order correlation approximation, the turbulent diffusion kernel becomes negative on large scales.
Key words: magnetohydrodynamics (MHD) - hydrodynamics - turbulence
Stars and galaxies harbor magnetic fields whose scales are larger than
those of the underlying turbulence.
This phenomenon is successfully explained in terms of mean-field dynamo theory
discussed in detail in a number of textbooks and reviews
(e.g. Moffatt 1978; Krause & Rädler 1980; Brandenburg & Subramanian 2005a).
In this context, velocity and magnetic fields are split into large-scale
and small-scale components,
and
,
respectively.
The crucial quantity of the theory is the mean electromotive force caused by
small-scale fields,
.
In many representations it is discussed under strongly simplifying assumptions.
Often the relationship between the mean electromotive force and the mean magnetic field
is tacitly taken both as (almost) local and as instantaneous;
that is, in a given point in space and time,
is considered as determined
by
and its first spatial derivatives in this point only.
In addition, the possibility of a small-scale dynamo is ignored.
Then the mean electromotive force is given by
In general, the mean electromotive force has the form
In this paper we ignore the possibility of coherent effects resulting from
small-scale dynamo action and therefore put
equal to zero.
For the sake of simplicity we assume the connection between
and
to be instantaneous so that the convolution
only refers to space coordinates.
The memory effect, which we thus ignore, has been studied
previously by solving an evolution equation for
(Blackman & Field 2002).
For homogeneous isotropic turbulence, we may then write,
analogously to (2),
At first glance, the representations (4) and (5) of
look rather different from (3).
Considering
and carrying out an integration by parts, we may
however easily rewrite (5) into
Finally, referring to a Cartesian coordinate system (x,y,z), we define mean fields
by averaging over all x and y, so that in particular
and
only depend on z and on time.
Then (5) turns into
Relation (8) can also be brought in a form analogous to
(6) and (7),
It is useful to consider in addition to (8) the corresponding Fourier representation.
We define the Fourier transformation in this paper
by
.
Then this representation reads as
In this paper, two specifications of the velocity field
will be considered.
In the first case
is chosen such that it corresponds to a steady Roberts flow,
which is periodic in x and y and independent of z.
A mean-field theory of a magnetic field in fluid flows of this type, which are of course different
from genuine turbulence, has been developed in the context of the Karlsruhe dynamo experiment
(Rädler et al. 2002a,b; Rädler & Brandenburg 2003).
It turned out that the mean electromotive force
,
except its z component,
satisfies relation (2)
if any nonlocality in the above sense is ignored (see also Appendix B).
Several analytical and numerical results are available for comparison with those of the present paper.
In the second case
is understood as homogeneous, isotropic, statistically steady turbulence,
for which the above explanations apply immediately.
Employing the method developed by Schrinner et al. (2005, 2007), we will in both cases
numerically calculate the functions
and
,
as well as
and
.
We first relax the assumption of isotropic turbulence used in the Sect. 1
(but will later return to it).
We remain, however, with the definition of mean fields by averaging over all x and y.
Then, as already roughly indicated above,
and
may only depend on z and time
but
,
because of
,
must be independent of z.
Furthermore, all first-order spatial derivatives of
can be expressed by the components of
,
that is, of
,
where
.
Instead of (8) we then have
In the following we restrict our attention to
and
and assume that
is equal to zero.
We note that
and the contributions of
to
and
are without interest for the mean-field induction equation,
which only contains
in the form
;
that is, they do not affect the evolution of
.
We may formulate the above restriction in a slightly different way by saying
that we consider in the following
,
,
and
,
as well as
,
,
and
only for
.
As for the mean-field treatment of a Roberts flow depending only on x and y(and not on z), we refer to the aforementioned studies
(Rädler et al. 2002a,b; Rädler & Brandenburg 2003).
Following the ideas explained there, we may conclude
that
and
with functions
and
of
,
and analogously
and
with functions
and
of k,
all for
.
For obvious reasons the same is true for homogeneous isotropic turbulence.
We calculate the
and
,
or
and
,
numerically by employing
the test-field method of Schrinner et al. (2005, 2007).
It was originally developed to calculate the full
and
tensors
(in the sense of (1))
for convection in a spherical shell.
Brandenburg (2005) employed this method to obtain results for stratified shear flow turbulence
in a local cartesian domain using the shearing sheet approximation.
More recently, Sur et al. (2008) calculated the dependencies of
and
in this way for isotropic turbulence on the magnetic Reynolds number,
and Brandenburg et al. (2008) calculated the magnetic diffusivity
tensor for rotating and shear flow turbulence.
However, in all these cases no nonlocality in the connection between
and
has been taken into account.
Following the idea of Schrinner et al., we first derive expressions for
with several specific
,
which we call ``test fields''.
We denote the latter by
and define
These relations allow us to calculate the
and
if the
with
for both
and
are known.
In preparing the numerical calculation, we start from the induction equation.
Its uncurled form reads
For calculating the
we are interested in the
,
which occur in response to the test fields
.
Specifying (21) in that sense we obtain
So far, no approximation has been made such as the second-order
correlation approximation (SOCA), also known as first order smoothing
approximation.
If we were to make this assumption, terms that are nonlinear in the fluctuations
would be neglected and (22) would simplify to
In the general case, as well as under SOCA,
the
and
are to be calculated from
.
More details of the numerical calculations of the
will be given below in Sect. 2.3.
Returning once more to (18), we note that the
depend
on both k and z introduced with the
.
As a consequence of fluctuating averages, they may also depend on time t.
The
and
however should depend on kbut no longer on z and t.
We remove the latter dependencies of our results by averaging
and
over z and t.
For the Roberts flow there should be no such z or t dependencies.
The relations (18) allow the determination of all components
of
and
with
.
We know already that
and
,
that is,
,
and
.
We may therefore determine
and
according to
and
by using the two test fields
and the relations (18) with i = j = 1 only.
We consider here a special form of a steady flow
that, in view of its dynamo action, has already been studied by Roberts (1972).
It has no mean part,
,
and
is given by
Next, we consider isotropic, weakly compressible turbulence and use an
isothermal equation of state with constant speed of sound, .
Considering first the full velocity field
,
we thus accept the momentum equation in the form
In addition to the momentum equation we use the continuity equation in the form
The relevant equations are solved in a computational domain of size
using periodic boundary conditions.
In the case of the Roberts flow (26), we fix L by
.
The test-field Eqs. (22)
with p=1,
,
and
(six equations altogether) are solved numerically.
With turbulence in the kinematic regime, the four Eqs. (27) and (28)
for
and
are solved, together with
these six test-field Eqs. (22).
Due to the finiteness of the domain in z direction and the periodic boundary conditions,
quantities like
and
have to be considered as functions that are periodic in z.
The Fourier integrals used for representing these quantities,
,
turn into Fourier series,
,
where
and the summation is over
For this reason only discrete values of k, i.e. k = kn, are admissible
in (13)-(18).
In this framework we may determine the
and
only for these kn.
As explained above, the test-field procedure yields
and
not as functions of k alone.
They may also show some dependence on z and t.
After having averaged over z, time averages are then taken over
a suitable stretch of the full time series where these averages are
approximately steady.
We use the time series also
to calculate error bars as the maximum
departure between these averages and the averages obtained from one of
three equally long subsections of the full time series.
In all cases the simulations were carried out using the
P ENCIL C ODE,
which is a high-order finite-difference code (sixth order in space and third
order in time) for solving the compressible hydromagnetic equations,
together with the test-field equations.
In the case of the Roberts flow, of course, only the test-field equations
are being solved.
Let us first recall some findings of earlier works, such as Rädler (2002a,b).
We use here the definitions
![]() |
Figure 1:
Dependencies of the normalized ![]() ![]() ![]() |
Open with DEXTER |
Figure 1 shows results for
and
obtained
both by general test-field calculations using (22)
and under the restriction to SOCA using (23).
These results for
agree completely with both (30) and (31),
and those for
agree completely with (30).
Unfortunately we have no analytical results for
beyond SOCA.
Proceeding now to
and
,
we first note that in SOCA,
as shown in Appendix C,
To obtain the results for the kernels
and
,
we have numerically calculated integrals as in (14)
using the data plotted in Fig. 2.
The results are represented in Fig. 3.
Again, analytical and numerical SOCA results are shown for comparison.
Note that the profiles
of
and
beyond SOCA
are rather narrow compared with those under SOCA,
and that of
even narrower than that of
.
![]() |
Figure 2:
Dependences of the normalized
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Open with DEXTER |
![]() |
Figure 3:
Normalized integral kernels
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Open with DEXTER |
Results for homogeneous isotropic turbulence were obtained by solving
the hydrodynamic Eqs. (27) and (28)
simultaneously with the test-field Eq. (22)
in a domain of size
.
The forcing wavenumbers
are fixed by
and 10.
Instead of the definitions (29), we now use
Figure 4 shows results for
and
with
.
Both
and
decrease monotonously with increasing |k|.
The two values of
for a given
but different
and
are always very close together.
The functions
and
are well represented by Lorentzian fits of the form
In Fig. 5 the kernels
and
are depicted, again with
,
obtained by calculating numerically integrals as in (14).
Also shown are the Fourier transforms of the Lorentzian fits,
![]() |
Figure 4:
Dependences of the normalized
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Open with DEXTER |
The results presented in Figs. 4 and 5
show no noticeable dependencies on .
Although we have not performed any systematic survey in
,
we interpret this as an extension of the above-mentioned results of Sur et al. (2008)
for
and
to the integral kernels
and
.
Of course, this should also be checked with higher values of
.
Particularly interesting would be a confirmation of different widths
for the profiles of
and
.
Our results are important for calculating mean-field dynamo models.
The mean-field induction equation governing
,
here defined as an average over x and y,
with
according to (8), allows solutions of the form
,
,
with
the growth rate
When using the definitions (29) for the Roberts flow or (34) for isotropic turbulence,
we may write (37) in the form
![]() |
Figure 5:
Normalized integral kernels
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Open with DEXTER |
Consider first the Roberts flow, that is, (38) with
.
Clearly
is non-negative in some interval
and it takes a maximum there.
Dynamos with
are impossible.
Of course,
depends on
.
With the analytic SOCA results (32), we find
for small
and that
grows monotonically with
,
approaching
unity in the limit of large
.
For small
,
a dynamo can work only
with small
,
that is, with scales of the mean magnetic field
that are much larger than the size of a flow cell.
Furthermore,
never exceeds the corresponding values for vanishing nonlocal effect,
which is
.
In that sense the nonlocal effect favors smaller k, that is, larger scales of the mean magnetic field.
With the numerical results beyond SOCA represented in Fig. 2,
with
,
we have
,
again a value less than unity.
In this case, too, a dynamo does not work with scales of the mean magnetic field smaller than that of a flow cell.
There is no crucial impact of the negative values of
for
on the dynamo.
We proceed now to isotropic turbulence and consider (38) with
.
Again,
is non-zero in an interval
and it takes a maximum there.
Some more details are shown in Fig. 6.
With the Lorentzian fits (35) of the results depicted in Fig. 4,
we find
for
,
and
for
.
In the limit of vanishing nonlocal effects
it turns out that
for
,
and
for
.
We have to conclude that dynamos are only possible if the scale of the mean magnetic field clearly exceeds
the outer scale of the turbulence.
In addition we see again that the nonlocal effect favors smaller k,
or larger scales of the mean magnetic field.
These findings may become an important issue, especially for nonlinear
dynamos or for dynamos with boundaries.
Examples of the last kind have been studied,
e.g., by Brandenburg & Sokoloff (2002)
and Brandenburg & Käpylä (2007).
In these cases, however,
the underlying turbulence is no longer homogeneous,
so the kernels
and
are no longer invariant under translations;
that is, they depend not only on
but also on z.
The finite widths of the
and
kernels may
be particularly important if there is also shear, because then there
can be a traveling
dynamo wave that may also show strong gradients
in the nonlinear regime (Stix 1972; Brandenburg et al. 2001).
![]() |
Figure 6:
Normalized growth rate
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
Open with DEXTER |
![]() |
Figure 7:
Mean magnetic field components
![]() ![]() ![]() ![]() |
Open with DEXTER |
For another illustration of the significance of a finite width
of the kernels
and
,
we consider a one-dimensional nonlinear mean-field model
with periodic boundary conditions.
We modify here the model of Brandenburg et al. (2001, Sect. 6)
with a dynamo number of 10 (corresponding to 5 times supercritical)
and
,
by introducing the integral kernels (36).
Figure 7 shows the components of the mean magnetic field
for two different values of
and for the conventional case
where the kernels are delta-functions.
Note that k1 corresponds to the largest scale of the magnetic field
compatible with the boundary condition.
It turns out that the magnetic field profiles are not drastically altered
by the nonlocal effect.
Low values of
,
however, correspond to smoother profiles.
Let us start again from
in the form (8).
We specify there, in view of isotropic turbulence,
and
according to (36),
and
represent
and
by Taylor series with respect to
.
A straightforward evaluation of the integrals provides us then with
The terms with derivatives of
in (39) can be interpreted in the sense of hyperdiffusion.
While all of them have the same signs in real space, the signs of the corresponding terms
in Fourier space alternate, which implies that every second term acts in an anti-diffusive manner.
Thus, a truncation of the expansion should only be done such that the last remaining term has even n,
or else anti-diffusion would dominate on small length scales
and cause
to grow beyond any bound.
There are several investigations in various fields in which hyperdiffusion has been considered. In the purely hydrodynamic context, Rüdiger (1982) derived a hyperviscosity term and showed that this improves the representation of the mean velocity profile in turbulent channel flows. In the context of passive scalar diffusion, Miesch et al. (2000) have determined the hyperdiffusion coefficients for turbulent convection and find that they scale with n like in Eq. (39). We are, however, not aware of earlier studies differentiating between diffusive and anti-diffusive terms.
We investigated the nonlocal cases presented in Fig. 7
using truncations of the expansion (39).
However, two problems emerged.
Firstly, terms with higher derivatives produce Gibbs phenomena,
i.e. wiggles in
,
so the results in Fig. 7 are not reproduced well.
Secondly, high-order hyperdiffusion terms tend to give severe constraints
on the maximum admissible time step, making this approach less attractive computationally.
It appears therefore that a direct evaluation of the convolution terms
is most effective.
The test-field procedure turned out
to be a robust method for determining turbulent transport coefficients
(see Brandenburg 2005; Sur et al. 2008; Brandenburg et al. 2008).
The present paper shows that this also applies to the
Fourier transforms of the integral kernels,
which occur in the nonlocal connection between mean electromotive force and mean magnetic field,
in other words, to the more general scale-dependent version of those transport coefficients.
For isotropic turbulence, the kernels
and
have a
dominant large-scale part and decline monotonously with increasing wavenumbers.
This is consistent with earlier findings (cf. Brandenburg & Sokoloff 2002),
where the functional form of the decline however remained rather uncertain.
Our present results suggest exponential kernels, corresponding to Lorentzian profiles
in wavenumber space.
The kernel for the turbulent magnetic diffusivity is about half as wide
as for the alpha effect.
This result is somewhat unexpected and would be worthwhile confirming
before applying it to more refined mean field models.
On the other hand, the effects of nonlocality only become really strong
when the scale of the magnetic field variations is comparable to
or smaller than the outer scale of the turbulence.
One of the areas where future research of nonlocal turbulent transport coefficients is desirable is thermal convection. Here the vertical length scale of the turbulent plumes is often comparable to the vertical extent of the domain. Earlier studies by Miesch et al. (2000) of turbulent thermal convection confirmed that the transport of passive scalars is nonlocal, but it is also more advective than diffusive. It may therefore be important to also allow for nonlocality in time. This would make the expansion of passive scalar perturbations more wave-like, as was shown by Brandenburg et al. (2004) using forced turbulence simulations.
Acknowledgements
We acknowledge the allocation of computing resources provided by the Centers for Scientific Computing in Denmark (DCSC), Finland (CSC), and Sweden (PDC). We thank Matthias Rheinhardt for stimulating discussions. A part of the work reported here was done during stays of K.-H. R. and M.S. at NORDITA. They are grateful for NORDITA's hospitality.
In view of (5)
we start with Eq. (3) for
,
put
and assume that
is a purely spatial convolution.
Applying then the Fourier transform as defined
by
,
we obtain
In view of (12) we start again from Eq. (3) and put
,
but we have to consider
now as a convolution only with respect to z.
Applying a Fourier transformation defined by
,
we obtain a relation analogous to (A.1),
A mean-field theory of the Roberts dynamo,
developed in view of the Karlsruhe dynamo experiment,
has been presented, e.g., in papers by Rädler et al. (2002a,b),
in the following referred to as R02a and R02b.
There a fluid flow like the one given by (26) is considered
but without any coupling of its magnitudes in the xy-plane and in the z-direction.
The mean fields are defined by averaging over finite areas in the xy-plane
so that they may still depend on x and y in addition to z.
As shown in those papers, when contributions with higher than first-order derivatives of
are ignored,
then
has the form
Let us start with the relation (B.2) and subject it to a Fourier transformation
with respect to z so that