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The paraxial expansion of a collisionless plasma jet into vacuum, guided by a magnetic nozzle, is studied with an Eulerian and non-stationary Vlasov-Poisson solver. Parametric analyzes varying the magnetic field expansion rate, the size of the simulation box, and the electrostatic potential fall are presented. After choosing the potential fall leading to a zero net current beam, the steady states of the simulations exhibit a quasi-neutral region followed by a downstream sheath. The latter, an unavoidable consequence of the finite size of the computational domain, does not affect the quasi-neutral region if the box size is chosen appropriately. The steady state presents a strong decay of the perpendicular temperature of the electrons, whose profile versus the inverse of the magnetic field does not depend on the expansion rate within the quasi-neutral region. As a consequence, the electron distribution function is highly anisotropic downstream. The simulations revealed that the ions reach a higher velocity during the transient than in the steady state and their distribution functions are not far from mono-energetic. The density percentage of the population of electrons trapped during the transient, which is computed self-consistently by the code, is up to 25% of the total electron density in the quasi-neutral region. It is demonstrated that the exact amount depends on the history of the system and the steady state is not unique. Nevertheless, the amount of trapped electrons is smaller than the one assumed heuristically by kinetic stationary theories.
Kinetic features and non-stationary electron
trapping in paraxial magnetic nozzles
G. S´anchez-Arriaga1, J. Zhou1, E. Ahedo1, M.
Mart´ınez-S´anchez2, J.J. Ramos1,3
1Equipo de Propulsion Espacial y Plasmas (EP2), Universidad Carlos III de Madrid,
28911 Legan´es, Spain
2Department of Aeronautics and Astronautics, Massachusetts Institute of
Technology, Cambridge, 02139, Massachusetts, USA
3Plasma Science and Fusion Center, Massachusetts Institute of Technology,
Cambridge, 02139, Massachusetts, USA
October 2017
Abstract. The paraxial expansion of a collisionless plasma jet into vacuum, guided
by a magnetic nozzle, is studied with an Eulerian and non-stationary Vlasov-Poisson
solver. Parametric analyses varying the magnetic field expansion rate, the size of the
simulation box, and the electrostatic potential fall are presented. After choosing the
potential fall leading to a zero net current beam, the steady states of the simulations
exhibit a quasi-neutral region followed by a downstream sheath. The latter, an
unavoidable consequence of the finite size of the computational domain, does not
affect the quasi-neutral region if the box size is chosen appropriately. The steady
state presents a strong decay of the perpendicular temperature of the electrons, whose
profile versus the inverse of the magnetic field does not depend on the expansion rate
within the quasi-neutral region. As a consequence, the electron distribution function is
highly anisotropic downstream. The simulations revealed that the ions reach a higher
velocity during the transient than in the steady state and their distribution functions
are not far from mono-energetic. The density percentage of the population of electrons
trapped during the transient, which is computed self-consistently by the code, is up to
25% of the total electron density in the quasi-neutral region. It is demonstrated that
the exact amount depends on the history of the system and the steady state is not
unique. Nevertheless, the amount of trapped electrons is smaller than the one assumed
heuristically by kinetic stationary theories.
PACS numbers: 52.75.Di,52.25.Xz, 52.65.Ff
Keywords: electric propulsion, magnetic nozzles, electron trapping Submitted to: Plasma
Sources Sci. Technol.
1. Introduction
Plasma expansions in the presence of magnetic fields appear in astrophysical scenarios,
such us pulsars [1], stellar winds [2] and supernova remmants [3], and in laser-produced
laboratory plasmas [4, 5]. They have also engineering applications in electric propulsion.
One of the most relevant is a magnetic nozzle [6], where a magnetic field generated
by coils is used to guide, expand, and accelerate the plasma without using any
physical wall. Several types of thrusters under development, including the helicon
plasma thruster [7], the magnetoplasmadynamic thruster [8], and the Variable Specific
Impulse Magnetoplasma Rocket (VASIMR) [9] involve magnetic nozzles. Plasma flows
in magnetic nozzles have been characterized in the laboratory by using laser-induced
fluorescence techniques [10], Langmuir and Mach probes [11] and spectroscopic methods
[12] among others.
The modeling of magnetic nozzles has also attracted great attention. One [13],
two [14, 15, 16, 17] and three [18] dimensional fluid models have been developed, and
the transformation of the internal energy of the plasma into directed kinetic energy,
the plasma detachment, and the role played by the plasma-induced magnetic field have
been discussed. However, since plasma flows are generally weakly collisional, simple
closures of the fluid equation hierarchy for the pressure tensor and the heat fluxes are
doubtful. A self-consistent determination of these magnitudes needs inevitably a kinetic
description of the plasma.
Stationary solutions of the Vlasov equation in a magnetized plasma expansion
have been obtained recently [19]. After assuming steady conditions, a slender nozzle
geometry, and a fully magnetized plasma, the conservation of the total energy and the
magnetic moment were used to write rigorously the densities of the particles connecting
with the source as functions of the electrostatic potential and to compute the latter. It
was then found that there exist regions in phase space not connected with either the
source or the downstream region where doubly-trapped bouncing particles can exist.
Since in collisionsless plasmas the filling of that regions happens during the transient,
a stationary model cannot characterize rigorously the (doubly) trapped particles. The
plasma spatial solution and its numerical convergence turned out to be very sensitive to
the distribution of trapped particles on the divergent side of the nozzle. After adding an
heuristic population of trapped electrons, the authors found numerical solutions with
the electron density dominated by the confined electrons over most of the divergent jet.
Discussions on whether or not trapped populations of electrons are an essential
component of the solutions and how they are determined also arise in other areas of
plasma physics. For instance, for an electron-attracting Langmuir probe in flowing
plasma, it was argued that a population of electrons should exist at the ram side
of the probe [20]. The formation of such a trapped population during the transient
phase, which is an adiabatic process, has been observed recently in non-stationary direct
(eulerian) Vlasov simulations [21]. Adiabatic trapping in slowly varying time-dependent
electric fields [22] has been considered in analytical studies of magnetized plasma
expansion [23]. Particles can also be trapped due to collisional effects. Particle collisions,
which can also produce trapped particles, have been included in non-stationary particle-
in-cell (PIC) simulations [24].
This work studies plasma expansions in magnetic nozzles by using a non-stationary
direct Vlasov code. As compared to stationary fluid models, this technique computes the
pressure tensor, the heat fluxes and the population of trapped electrons self-consistently.
PIC codes do also exhibit these two features. However, due to the numerical noise, they
do not give an accurate description if the number of macroparticles per cell is small, a
circumstance that is unavoidable in non-stationary simulations of a plasma expansion
into vacuum. Direct Vlasov codes, which are more demanding from a computational
point of view because they discretize the distribution function in real and velocity
spaces instead of using macroparticles, provide a better accuracy and degree of detail of
the distribution functions. Section 2presents the mathematical model and describes
briefly the numerical algorithm. The effects of fixing in the code the size of the
nozzle (finite simulation domain) and the electrostatic potential value at the exit, two
parameters that do not appear or are not externally imposed in a real infinite plasma
expansion, are shown in Sec. 3. The correct selection of these two parameters allows to
reproduce with the code the conditions of a real nozzle with zero net current. Section
4shows some kinetic features of the expansion such as the distribution functions, and
particle densities, temperature, and heat fluxes. The trapped electron population is
computed and the results are compared with previous studies. Section 5summarizes
the conclusions of the work.
2. Magnetic nozzle model based on guiding center theory
2.1. Plasma model
Let us consider a tank placed at z < z0<0 and filled with an electron-ion plasma
(see Fig. 1). We are interested in the time-dependent, magnetically-channeled plasma
expansion that is produced when a hole of radius R0at z=z0is opened at the plasma-
vacuum wall. For the sake of illustration, the geometry of the magnetic nozzle is the
one corresponding to a current loop of radius RL(RL> R0) placed at the plane z= 0.
It generates a stationary and non-uniform magnetic field in the vacuum region that
reaches its maximum value BTat z= 0 (the nozzle throat T). The forward distribution
functions of ions and electrons entering the nozzle are assumed semi-Maxwellian,
fα(t, z =z0, vk>0, v) = N mα
exp mαv2
α!, α =i, e, (1)
while the backward distribution functions will be determined self-consistently by the
expansion characteristics. Here Nand T
αare reference parameters (not the actual
densities and temperatures at z=z0that also involve the backward distribution
function), v=qv2
is the velocity, and vkand vthe velocity components
parallel and normal to the magnetic field lines. For convenience, hereafter the axial
coordinate, time, velocities, magnetic field, electrostatic potential, particle distribution
functions, and densities, are all normalized and we will write z
De z,
pe t,
pe vk,,B/BTB,eφ/kBT
e)3/2fα, where
De =q0kBT
e/Ne2is the Debye length, ω
pe =qNe2/me0the electron plasma
frequency, kBthe Boltzmann constant, methe electron mass, ethe elementary charge,
and 0the vacuum permittivity. As shown below, the plasma dynamics depends on the
following dimensionless parameters in our model
, δαT
, βαmα
, Zα,(2)
where the subscript α=e, i denotes electrons and ions, and mαand Zαare the mass
and the charge number of the α-species.
- z00zM
N*, Te
*, Ti
Figure 1. Geometry of the convergent-divergent magnetic nozzle.
In this work we follow a paraxial approximation and assume a slender and slowly-
varying magnetic field, i.e. we take RL/R0>> 1, and just look at the center line of the
magnetic nozzle. Under this hypothesis, the parameter R0does not appear anymore in
the model and one just needs the normalized magnetic field at the center line. It reads
B(z) = r3
where 1zis an unit vector along the z-axis. Therefore, we are having a convergent-
divergent nozzle with the maximum of the magnetic field B= 1 at z= 0 and B0
as z→ ±∞; the analysis here will be focussed at the divergent side of the nozzle. The
model also assumes that the magnetic field is very strong and the normalized Larmor
radii satisfies ρβv/|Zα|B << rL. In the limit ρ/rL0, the slow drift motion of
the particles across the field lines can be ignored and the normalized magnetic moment
is conserved (for brevity, we will generally write µαµ). Hereafter, we will work with
the gyrocenter variables (z, vk, µ, γ), and will also average the distribution functions of
the particles fαover the fast gyrophase γ
fα(t, z, vk;µ) = 1
fα(t, z, vk, µ, γ). (5)
The evolution of the gyrocenter distribution function ¯
fαis governed by the Vlasov
∂t +vk
∂z +aα
= 0,(6)
where we ignored the induced magnetic field and introduced the parallel dimensionless
βα Zα
∂φ (t, z)
∂z +µdB (z)
dz !(7)
The normalized electric field E=EkB/B =∂φ/∂z is given by the paraxial Poisson’s
∂z Ek
with the particle densities computed from the distribution functions as
nα(z) = Zfαdv=2πB
−∞ Z+
fαdvkdµ. (9)
Therefore, the dynamics of the electrons and the ions governed by the two Vlasov
equations in Eq. (6) are nonlinearly coupled through the electrostatic potential. This
set of equations must be integrated with appropriate boundary and initial conditions,
discussed in Subsec. 2.3.
2.2. Evolution of macroscopic quantities
The evolution equations of the main macroscopic quantities are helpful in the analysis
of the simulations. The average or mean value of any quantity ψ, is computed as
−∞ Z+
Interesting quantities are: densities given by Eq. (9); macroscopic velocities parallel
to the magnetic field uα=DvkEα; current densities jα=Zαnαuα; temperatures
kαEαand Tα=Bhµiα, where we introduced the peculiar velocities
ckα=vkuα; pressures Pkα=nαTkαand Pα=nαTα; and (parallel) heat fluxes
of parallel and perpendicular energy, Qkα=1
kαEαand Qα=BnαDµckαEα,
respectively. According to Sec. 2, the normalization has been done with characteristic
variables involving the electron mass.
The evolution equations of these quantities are obtained straightforwardly by taking
velocity moments in Eq. (6). In the paraxial case, the equations for continuity, axial
momentum, total energy, and perpendicular energy are, respectively,
∂t +B
∂z nαuα
B= 0,(11)
∂t (βαnαuα) + B
∂z βαnαu2
+"PkαPαln B
∂z Pkα
∂z #,(12)
∂t "nα βα
∂z "nαuα
B βα
∂z = 0.(13)
∂t (nαTα) + B2
∂z 1
B2(nαuαTα+Qα)= 0,(14)
This set of macroscopic equations is incomplete, unless equations for the parallel heat
fluxes Qkαand Qαare added, which will introduce higher order magnitudes. A closure
of the set of the fluid equations is not simple in a collisionless plasma.
Here, the consistent kinetic solution is obtained directly, so the fluid equations are
used to interpret the results, mainly the steady-state ones in Section 3. In this respect,
in the above equations, 1/B plays the role of the effective beam area. Furthermore, it is
in fact the natural spatial variable (instead of z) in the divergent paraxial nozzle. Thus,
in (11), nαuα/B is the species flow (i.e. the flux area integrated), which is constant
spatially in steady-state. The species current, jα/B, and the total plasma current,
I= (je+ji)/B, are constant in steady-state too. In (12), the two last terms on the
right-hand side are the contribution of the divergence of the pressure tensor (i.e. the
net pressure force). Then, the steady-state limit of (13) yields that the total enthalpy
flow, ˙
Hα, is constant spatially,
B βα
B=const (15)
Here, (Qkα+Qα)/B is the total heat conduction flow. The steady state limit of
(14) yields that the (convection plus conduction) flow of perpendicular energy evolves
proportional to B1
B2=const, (16)
which is the direct consequence of the conservation of the magnetic moment of the
species. These conservation laws were already used in Ref. [25] to analyze the plasma
response in a convergent magnetic field. Finally, if the mean kinetic energy is eliminated
from (13) by using equations (11) and (12), the evolution equation for the internal energy
is obtained,
∂t Pkα
∂z 1
2Pkα+Pα+ (Qkα+Qα)
∂z +PαPkαln B
∂z #= 0,(17)
which can susbtitute for (13).
2.3. Simulation domain and boundary conditions
We are interested in the time-dependent plasma expansion along the (semi-infinite)
divergent nozzle, extending from z= 0 (the throat T) to z=. However, since the
numerical simulation requires to work with a finite domain, the downstream end of the
domain (point M) will be placed at a certain zM1, with BM<< 1. A parametric
analysis of the combined influence of zMand rLon the solution is carried out below.
Furthermore, it turns out that, in spite of applying quasineutrality at the upstream
end of the simulation domain, a non-desirable Debye sheath, extending a few Debye
lengths develops there. In order to eliminate its spurious influence, the usptream end
of the domain has been placed at the convergent side of the nozzle, in particular, at
At the domain entrance, we set Maxwellian functions for the injected particles,
fα(t, z =z0, vk>0; µ) = χα(t)¯
fMα (18)
fMα = βα
exp βαv2
and χe= 1. The parameter χi(t) is dynamically varied to accomplish quasineutrality
at entrance section z=z0, once reflected-back particles are taken into account there.
(For instance, if no ions are reflected back and all electrons are, χi= 2.) At the domain
downstream end, in order to simulate the vacuum at infinity, we impose no incoming
particles into the domain,
fα(t, z =zM, vk<0; µ)=0.(20)
Regarding initial conditions, one would initially set ¯
fα(t= 0, z > z0, vk;µ) = 0.
However, since such a hard transition can lead to numerical issues, our simulations used
fα(t= 0, z > z0, vk;µ) = ¯
fMα ×exp zz0
with L0a dimensionless parameter that controls the density gradient of the initial plasma
profile. A value L0= 2, which yields a profile with width about a few Debye lengths, is
enough to provide a smooth transition at t= 0 in the simulations.
Finally, Poisson’s equation requires two boundary conditions on the electrostatic
potential. Clearly, there is the freedom to take φ(z=z0) = 0. With respect to the
boundary condition at the downstream end, the studies of the semi-infinite, stationary
nozzle with a simple plasma have shown two things. First, the potential decays
monotonically to an asymptotic value φ=φ<0 (i.e. yielding dφ/dz|0). Second,
the net electric current of the plasma beam Iis not a parameter independent of φ:
a parametric current-voltage curve I(φM) with I/∂|φM|>0 exists. This behavior of
the current-voltage curve is simple to explain: for normalized distribution functions at
injection, the more negative is φ, a larger fraction of electrons injected into the nozzle
is reflected back to the reservoir while (near) all ions cross freely the nozzle, and thus
the more positive becomes I. Therefore, in the downstream end of our finite simulation
box we can impose either φM=φ(zM) or I. The first choice is the natural one for the
numerical scheme. The case of most practical interest, I= 0, which corresponds to a
current-free plasma beam, requires to iterate on φM.
2.4. Direct Vlasov solver
This section discusses briefly the main features of the novel direct Vlasov code
VLASMAN (VLAsov Simulator for MAgnetic Nozzle), that has been developed for
the numerical integration of (6). A mesh of points ziwith i= 1,...Nzis defined within
the interval z0zzM. These points are distributed non-uniformly in order to keep
constant the ratio between the resolution of the mesh and the local Debye length, which
is expected to vary as λDe n1/2B1/2. The velocity space, involving vkand µ,
was truncated as vα
max vkvα
max and 0 µµα
max and discretized with Nvk×Nµ
points. Unlike the spatial mesh, which is common for both species, different maximum
velocities and magnetic moments are chosen for electrons and ions. For both species, the
velocity mesh is uniform. The unknowns of the code are the values of the distribution
functions at the points of the mesh and at discrete times tm,¯
fα(tm, zi, vkj, µk).
Since µappears as a parameter in (6), the algorithm just needs to solve a one
dimensional equation Nµtimes. Given the distribution function ¯
fα(tm, zi, vkj, µk), the
value at tm+ ∆tis found by using a splitting algorithm that treats the convective terms
in the zand vkdirections separately, and gives a scheme of second order in ∆t[26]. A
short summary of the splitting algorithm and a description of the numerical schemes
implemented for the interpolation and the numerical integration are given in Appendix
In the simulations, we took the physical parameters δi= 1, βi= 100, Zi= 1
and considered several values of rL. The value of βiis not realistic for an electron-
ion plasma but it still separates significantly the electron and ion response times and
helped us save computational resources. Regarding the geometry of the nozzle, we set
z0=rL/2, i.e. the divergent and convergent segments have lengths equal to rL/2 and
zM, respectively. The most relevant numerical parameters are Nvk= 77, Nµ= 101,
max = 5, vi
max = 0.5, µe
max =µi
max = 12.5, and ∆t= 0.03. Tradeoffs analysis varying
the numerical parameters zMand φMare shown in Sec. 3.
3. Stationary solution and parametric analysis
The effect of the truncation of the computational box up to a length zMand the
setting of the electrostatic potential value φMat that position have been investigated
by running a large number of simulations. After taking an expansion rate of rL= 50,
the physical and numerical parameters explained in Sec. 2.4, and several values of
zMand φM, we integrate the Vlasov-Poisson system forward in time until the plasma
reached the corresponding stationary state. For each simulation, the latter was verified
by monitoring the time evolution of the most important variables, such as density and
potential, and the z-profiles of nαuα/B, which becomes uniform at stationary conditions.
-0.04 -0.02 0 0.02 0.04 0.06
Figure 2. Net current-to-magnetic field ratio j/B versus the total potential drop
(φM) and the one between the throat and zM(φT M ) for several expansion rates and
box sizes. The curves practically overlap, also for the case rL= 100 (not shown)
First of all, Figure 2shows the results of investigating the influence of the total
potential fall φMon the electric current Iacross the nozzle in steady-state. As expected
and known from previous models, the current I(abcissa) is positive for large, negative
values of φM(ordinate), and negative otherwise. The most relevant result here is the
universal character of the curve φM(I): it is practically independent of rLand zM(as
long as BM1), which allows to infer that this curve reproduces the behavior of
the semi-infinite nozzle too. Furthermore, Fig. 2shows that the curve φT M (I) for
the potential fall along the divergent part of the nozzle is (near) universal too. The
principal, current-free beam case has potential falls of φM≈ −2.75 and φT M ≈ −2.34.
Such potential drops are consistent with previous calculations from stationary kinetic
models (extrapolate to mi/me= 100 the results in Fig. 4c of Ref. [19]). Hereafter, we
focus the analysis at discussing the (approximate) ’current-free case’ φM=2.75. The
steady states values of the normalized species current are Ii=Ie'0.074
Figure 3shows (near) stationary axial profiles for different rLand zM. Panel (a)
plots the relative space charge for rL= 50 and several lengths of the simulation box;
panels (b) and (c) plot the electric potential profile versus zand B1, and panel (d) the
ion density versus B1. Three different spatial regions can be distinguished in panels
(a)-(c). First, a small sheath (with a relative space charge <5% and extending a few
Debye lengths) forms at the entrance of the simulation domain, in spite of having forced
quasineutrality locally at z=z0. This ’numerical’ sheath is caused by the need of the
electric field to adapt the entrance distribution functions of ions and electrons and it
was the reason to include a small convergent part of the nozzle, even though the work
is focused on the divergent nozzle behavior. Second, there is the large quasineutral
region, with a decreasing electric field as we move downstream. Third, there is a second
0 200 400 600 800
0 200 400 600 800
Figure 3. Panels (a), (b) and (d) show, respectively, the normalized space charge,
φversus zand niversus 1/B for rL= 50 and several zM. Panel (c) displays φversus
1/B for zM= 800 and several expansion rates.
Debye sheath at the downstream end of the simulation. Since the Debye length is
proportional to n1/2
α[and thus nearly proportional to B1/2, according to panel (d)], it
increases by 1-2 orders of magnitude along the discharge, thus giving the impression that
the downstream sheath is thick. Just for reporting, the relative space-charge and the
potential fall in the downstream sheath are nearly constant, because of the low electric
field at the sheath entrance and the need to adjust the total potential fall to φM. Panel
(c) shows that φdepends more naturally on B1in the quasineutral region. In panel
(d), we see that niis near proportional to B, indicating a much gentler dependence of
uion B(to have niui/B=const). The electron density nebehaves as niexcept at the
downstream sheath where it decreases more sharply. Normalized plasma densities at the
entrance and the throat are ne0= 0.97 and neT = 0.62, the difference indicating the jet
acceleration in the small convergent region of the nozzle. Finally, at the simulation box
entrance, the ratio of ion-to-electron densities for forward moving particles, that is χiin
(18) is 1.53: this ratio would be close to 2 and 1 if the entrance would be, respectively,
at the throat and further upstream in the convergent magnetic nozzle.
The stationary momentum equation of ions and electrons, (12), states the balance
between the inertial force (or flow of species momentum) FI
α, the pressure force FP
α, and
the electric force FE
α. Both FI
αare positive, both FP
αare expected to be positive, while
i>0 and FE
e<0. Furthermore, one has: FE
iin the quasineutral region; and
Figure 4. Stationary, spatial profiles of inertial, pressure, and electric forces of ions
and electrons for rL= 50 and zM= 800.
e/F I
ime/mi1 for the current-free and ’small current’ cases. The combination
of these two facts implies that the electron inertia is negligible, and the electric and
electron pressure forces balance each other, i.e. FP
e' −FE
e. For ions, the inertial
force is dominant, and the relevance of the ion pressure depends on upstream conditions
for Ti/Te. These trends are confirmed by Figure 4(a), which plots FE
e, and FI
the two other forces are obtained by just applying (22). In this case the ion flow is
supersonic and thus accelerated freely by the electric force.
Figure 4(b) assesses the different contribution to the net electron pressure force,
that is the pressure tensor divergence. This can be expressed in two different ways:
∇ · ¯
∂z +PαPkαln B
∂z B
∂z (Pkα
B) + Pα
ln B
∂z .(23)
The first division is based on the parallel pressure gradient and the magnetic mirror
effect, and the second is based on the Pkαand Pαcontributions. The panel
shows, interestingly, that the parallel pressure gradient and the magnetic mirror effect
are individually much larger than their difference (i.e. they compensate practically
each other). This makes them not very suitable to characterize the total pressure
contribution. On the contrary the Pkαand Pαcontributions are of the same order
as their difference. For this particular case, the Pα-contribution dominates mildly
upstream, while the Pkα-contribution dominates totally downstream. The milder
behavior of the z-derivative of Pkα/B compared to that of Pkα, and the drop of the
Pα-contribution, are due to nαBapproximately and the behaviors of Tkαand Tα
shown below. Although not shown, the ion pressure contributions behave in the same
way as the electron ones.
Figure 5(a)-(c) displays the stationary spatial profiles of the parallel and
perpendicular temperatures of ions and electrons for zM= 800 and rL= 25,50, and 100.
In this collisionless plasma, these kinetic temperatures simply express the dispersion of
particle velocities. The first interesting feature is that both perpendicular temperatures
decrease with B1, a behavior related to the conservation of magnetic moment. On the
contrary, the parallel temperatures are rather constant spatially, except for the decrease
0 200 400 600 800
0 200 400 600 800
Figure 5. Panels (a) and (b) show the perpendicular temperature of the electron and
the ions, respectively.Panel (c) shows their parallel temperatures and (d) the mean
kinetic energy of the ions. zM= 800 and solid, dashed, and dot-dash lines correspond
to rL= 100,50, and 25, respectively.
of Tkeat the downstream sheath. Therefore, the plasma expansion along the divergent
nozzle implies both anisotropy and cooling [the average temperature is (Tkα+ 2Tα)/3].
This behavior agrees qualitatively with stationary, kinetic, fully-quasineutral models (see
figure 7 in [19]). Apparently, the main difference of the non-stationary model, which
computes the population of trapped electrons self-consistently, is a softer decay of the
parallel temperature. Values of normalized temperatures at the throat are TkiT '0.30,
TiT '1.20, TkeT '0.86, TeT '0.90, and they are explained by the analysis of Ref.[25]
for a convergent magnetic geometry: there the ion distribution function is determined
by the combination of the magnetic mirror and the free extraction at the throat, while
electrons remain near Maxwellian. Figure 5(d) displays the ion axial kinetic energy,
which increases downstream thanks to the electric potential energy. For this current-
free case, the electron axial energy behaves exactly the same in the quasineutral region
(but it is me/mitimes lower).
Figure 6analyzes the z-profiles of the heat (or internal energy conduction) flows.
We recall that Qkand Qrepresent parallel fluxes of the parallel and perpendicular
thermal energies (perpendicular fluxes are zero in our model). Notice that, since this
is a collisionless plasma, no Fourier-type law is expected to apply for these heat flows.
Panel (a) shows that: the area-integrated parallel heat flows, Qkα/B, are approximately
constant (except, as often, near the ends of the simulations) while the parallel flow
of perpendicular thermal energy, Qα/B, decrease proportional to B2. The same
dependence with Bwas found for the internal energy convection flows, nαuα(3Tkα/2)
0 100 200 300 400 500 600 700 800
0 100 200 300 400 500 600 700 800
Figure 6. Axial profiles of the heat fluxes [panel (a)] and their relative rates versus
the pressure fluxes [panel (b)] rL= 50 and zM= 800.
and nαuαTα. To complete this, panel (b) determines the relative rates of internal
energy conduction versus the pressure flux for ions and electrons. Focusing on the
main quasineutral region, conduction of parallel and perpendicular internal energies of
electrons is about 50-52% of its convection; for ions conduction represents 4% and 11% in
the parallel and perpendicular cases; more parametric analyses are needed to ascertain
how these values depend on the upstream plasma conditions. In spite of this, it seems
clear that, both for ions and electrons, the flow of the perpendicular internal energy
decreases in proportion to B, Eq. (16), and becomes negligible downstream. Then,
since the total enthalpy flow is conserved, Eq. law (15), that loss of perpendicular
energy goes mainly into increasing the axial kinetic energy, which is the macroscopic
equivalence of the classical particle mirror effect, for ions, and the electric potential
energy for electrons.
4. Kinetic features of the expansion
There are several ways of presenting the four-dimensional distribution functions
fα(t, z, vk, µ) and each of them highlights a particular physical feature of the plasma
expansion. For instance, as shown in Figs. 7and 8, the development of the plasma
plume structure is evident when fαis plotted versus the axial distance and the parallel
velocity for a given value of µand t. In panels (a)-(c) of Fig. 7, which corresponds to
that representation with µe= 1 and t= 500, 2000, and 7200 for rL= 50 and zM= 800,
one can observe how the simulation box is filled progressively by the plasma. Note that
our simulations used ve
max = 5 but we only showed the range 3vke3 for clarity.
As shown by the red line, the distribution feis not symmetric with respect to the axis
vke= 0; for a given z, there are more outgoing electrons than reflected ones. As shown
in panel (c), the depletion of particles with negative velocity as zincreases gives rise to
a lower dispersion in vke, thus producing the moderate drop in Tkedisplayed in figure 5.
Figure 7. Panels (a), (b), and (c) show the electron distribution function for µ= 1
and times t= 500, 2000 and 7200, respectively, for rL= 50 and zM= 800. The red
line corresponds to vke= 0.
The distribution functions of ions with magnetic moment µi= 1 and times t= 500,
2000 and 7200 are shown in figure 8. For convenience, we did not plot the full dynamic
range of the simulation (0.5vki0.5) but only the region of interest. Panels
(a)-(c) reveal that ions reach higher velocities during the transient than in stationary
conditions. Once the plume reached its equilibrium state [panel (c)], most of the
acceleration happens within the first sixty Debye lengths from the throat [consistently
with the electrostatic potential profile of panel (c) in Fig. 3]. Although there is a certain
amount of dispersion, the ion distribution function is not far from mono-energetic.
Figure 8. Panels (a), (b), and (c) show the ion distribution function for µ= 1 and
times t= 500, 2000 and 7200, respectively, for rL= 50 and zM= 800. The red line
corresponds to vki= 0.
4.1. Trapped electrons
One of the main features that distinguishes the non-stationary code VLASMAN from
other codes is the self-consistent computation of the doubly-trapped particles (electrons,
here). A detailed analysis of this population is carried out by noting first that the
characteristic equations of the Vlasov equation
dt =vk,(24)
dt =aα(z, t, µ),(25)
give the following evolution law for the particle total energy E=βαv2
k/2 + Zαφ+µB
dt =Zα
∂t .(26)
Therefore, in stationary conditions (φ/∂t = 0), the energy is also conserved. In the
steady state and for a given energy and zposition, the maximum value of the magnetic
µmax (z, E ) = EZαφ
is found by setting vk= 0 in the definition of the energy. A particle of energy Eis
trapped between two axial coordinates zmin zzmax if its magnetic moment µ
intersects the curve of µmax at those points, i.e. µmax (zmin, E) = µmax (zmax , E) = µ.
For this reason, the analysis of the trapped particles is easier with the parametrization
fe(t, z, E, µ), instead of fe(t, z, vk, µ). Since for a given energy there are two possible
velocities vk=±q2 (EZαφµB)α, the total distribution function fe(t, z, E, µ)
involves outgoing f+
e(vk>0) and ingoing f
e(vk<0) distribution functions. In the
analysis below we will always refer to the total one.
Panels (a)-(c) in Fig. 9show the electron distribution function versus zand µfor
E= 2.1 and times t= 500, 2000 and 7200. At large t[panel (c), considered as steady
state], the curve µmax (upper red solid line) exhibits a minimum, say µ, at a position z
close to the throat. For this energy level, two populations of electrons exist in the steady
state. First, reflected electrons, with µ<µor µ>µand z < z: they are injected
from the left of the simulation box, propagate to the right until the location where
µ=µmax, where vk= 0, and they are reflected back to the nozzle entrance and the
reservoir. Second, trapped electrons, with µ > µand z > z, which bounce between
two axial coordinates satisfying µmax (zmin, E) = µmax (zmax, E) = µ. Physically, in
the divergent nozzle, electrons injected upstream gain parallel velocity from the (anti)
mirror effect in the decaying Band lose it from the electrostatic force. Therefore, their
reflection is always due to the dominance of the electrostatic force. The same type of
arguments apply to the bouncing motion of the double-trapped electrons.
Similarly to panel (c), panel (d) shows the steady-state distribution function for
electrons of a higher energy (E= 3), µmax(zmax )>0. In this case, there is a population
of free electrons with µ < µthat leave the computational box together with the ions,
there is a small region of reflected electrons, there are no doubly trapped electrons, and
the region µ>µand z > zwill be totally void of electrons at t→ ∞. Hereafter we
will denote the doubly-trapped, reflected and free electrons with the subscripts et,er,
and ef, respectively.
The filling of the regions of the phase space with trapped particles, which is not
connected with the injection zone (z= 0) at stationary conditions, is explained in terms
of two transient mechanisms. Since the curve µmax and its minimum µdepend on time,
an electron moving to the right with µ<µat a given time could be trapped if it meets
the condition µ>µwhen moving backwards after electrostatic reflection. The other
mechanism cannot be visualized in the µzplane because it is related to the transport
of particles along a third dimension (the energy is not conserved during the transient).
A particle, with energy Ejat instant tjand non-trapped in the µzdiagram with
E=Ej, could be trapped at a latter instant tkif its energy decreases to a value Ekthat
traps the particle at the µzdiagram with E=Ek< Ej. Both mechanisms, which
can trap or untrap the particles, act simultaneously during the transient period of the
Figure 9. Electron distribution functions in the µezplane for several values of
Eand t. Simulations results for rL= 50 and zM= 800. The red line corresponds to
µmax in equation 27 and µ=µ.
In order to assess the relative importance of the three populations of electrons we
analyzed the distribution function at the end of the simulations with rL= 25,50, and
100. From the zµdiagrams for all the energies involved in the simulations, the densities
of the trapped (net), free (nef ), and reflected (ner ) electrons were found. The results
are displayed in the three panels of Fig. 10, which show the densities versus the inverse
of the magnetic field. In the extensive quasineutral region the three densities are of the
same order and the trapped electrons represent about 20% of the total. Such a value
shows that the population of trapped electrons is neither dominant nor negligible. In
any case, it is smaller than the one assumed heuristically by a recent stationary kinetic
model, which filled completely the phase-space region where doubly-trapped electrons
could potentially exist [19]. At the downstream sheath, where only the most energetic
electrons can arrive, the density of the free electrons is clearly dominant but the density
of trapped electrons still has a finite value.
rL=100 rL=50
rL=50 rL=25
Figure 10. Panels (a), (b), and (c) show the electron densities of the trapped, free,
and reflected electrons for zM= 800. Solid, dashed, and dot-dashed lines correspond
to rL= 100,50, and 25, respectively.
The results of the code Vlasman can be post-processed to investigate more advanced
features related with the trapping of the particles. For instance, once a simulation is
finished and the history of the electrostatic potential φ(z, t) and the distribution function
of the electrons in the steady state Fe(z, vk, µ, tF) are known, the trajectories of the
trapped particles can be computed as follows. First, by using the zµdiagrams of
Fe(z, vk, µ, tF) for all the energies, we computed the distribution function Fet(z, vk, µ, tF)
of the trapped electrons at the end of the simulation. Then, taking the values of zand
vkof the trapped electrons as initial conditions, we integrated numerically Eqs. 24-25
backward in time with the corresponding value of µas a parameter and taking into
account the computed time history of the accelerations. Panel (a) in Fig. 11 shows two
examples of trapped orbits for rL= 50 and zM= 800. When analyzed from t=tF
to t= 0, they exhibit periodic motions that correspond to the trapped phases in the
steady state, and then a segment that connects them to the entrance of the nozzle at
the z=z0. For one of the orbits, panel (a) shows the time at different points of the
trajectory. We observe that this particular trapped electron is injected at t= 1287
and the characteristic time to complete a periodic motion is 1500. This bouncing
time depends on the energy and the magnetic moment of the electrons and, for some of
them, it can be affected by the size of the computational box. We also mention that,
as t→ ∞, the orbits of the trapped particles are periodic because, once the stationary
state has been reached and φdoes not depend on time, Eqs. (24)-(25) are autonomous
and integrable. In our analysis, we computed the 105trapped trajectories with the
highest values of the distribution function in the simulation for rL= 50 and zM= 800.
From them, the values of the parallel and perpendicular velocities of the particles when
they were injected at z=z0and the injection time tinj were found. The color in panel
(b) of Fig. 11 shows the value of the electron distribution function at z= 0 given by
Eq. (18) in the vkeveplane, and the red dots the region of the phase that yields
trapped trajectories in the interval tinj t < tF. The figure shows that there is a
single phase space region for trapped particles in the injection and it is centered about
(vke, ve)(2,2). Almost the same region was found in the simulation with rL= 25
and zM= 800.
Each red point in panel (b) produces a set of trapped orbits during a certain
interval of time. Beyond a certain time, particles cannot be trapped anymore because
the system reaches the steady state and the orbits cannot connect with the trapped
regions showed in Fig. 9. In order to investigate the injection time distribution of the
trapped trajectories we constructed a histogram. As shown in panel (c) of Fig. 11, we
summed the values of ¯
feof the particles trajectories that were injected within a certain
temporal interval of width ∆t= 200. The histogram shows that particles injected at the
very beginning of the simulation are not trapped, and the contribution of the trapped
particles injected after t4000 is negligible. It reveals a complex behavior with several
maxima and minima and highlights the non-linear character of the transient phase.
Figure 11. Trapped particles results for rL= 50, zM= 800, and φM=2.75. Panel
(a), (b) and (c) shows two trapped trajectories, the region of the phase space at z= 0
that yields trapped electrons within the time Tinj tTF, and the histogram of the
injection time, respectively.
Since the trapping happens during the transient phase and there is an infinitude of
possible scenarios describing the turn on of the nozzle, the natural question about the
robustness of the previous results arises. This topic has been investigated by running
a simulation with rL= 25, zM= 800, and the following boundary condition for the
electrostatic potential
φM(t) = φ0+ (φFφ0)1
πarctan [ω(tt0)],(28)
where we took the parameters φ0=5, φF=2.75, ω= 0.1, and t0= 2000.
Such a law keeps the potential at the exit of the simulation box roughly equal to
φ0=5 before t0= 2000, then makes a smooth transition to the current-free condition
φM=2.75, and keeps this value constant afterwards. Interestingly, for this simulation,
the maximum percentage of the density of trapped particles (27%) is greater than the
one obtained when φMis constant [about a 20% as shown by panel (a) in Fig. 12]. As
shown in panels (b) and (c), the regions of the phase space at z=z0that are trapped at
later times and the histogram are also different from the ones obtained for constant φM.
We then conclude that the steady state of a collisionless plasma expansion in a magnetic
nozzle is not universal and depends on the particle history of the system. On the one
hand, this justifies the uncertainties related to the trapped population in steady-sate
models. On the other hand, this enhances the relevance of taking into account collisions,
even if they are very rare, since they could be the mechanism leading to a final, unique
distribution for the doubly-trapped population and a unique steady-state solution.
0 2000 4000 6000 8000
60 (c)
0.2 (a)
Figure 12. Trapped particles results for rL= 25, zM= 800, and φMgiven by Eq.
28. Panel (a), (b), and (c) show the relative density of the trapped population, the
region of the phase space at z= 0 that are trapped within the time tinj ttF,
and the histogram of the injection time, respectively. For comparison panel (a) also
reproduces the relative density of the trapped population for the case φM=const.
5. Conclusions
The Vlasov-Poisson solver revealed interesting kinetic features of the unsteady paraxial
expansion of collisionless plasma jets in magnetic nozzles. Its most relevant properties,
i.e. its non-stationary character and the discretization of the Vlasov equation on a mesh
in phase space, provided a self-consistent description of the particles trapped during the
transient with a high accuracy. The parametric analysis showed how the electrostatic
potential drop and the size of the simulation box should be selected to reproduce relevant
physical conditions in the simulations. In general, the results are aligned with previous
work based on stationary models, which considered a heuristic population of trapped
particles. Such results include the electrostatic potential drop that yields a zero net
current, the main features of the electron cooling (temperatures and heat fluxes), and
the shape of the ion distribution function that is close to monoenergetic. Interestingly,
the profiles within the quasineutral region of several quantities, such as the normal
electron temperature and the particle densities, do not depend on the expansion rate if
presented versus the inverse of the magnetic field.
The analysis provided quantitative information about the relative importance of the
different electron populations. Reflected electrons are the dominant population in the
quasineutral region, followed by the free and the trapped electrons. The latter represent
about 20% of the total. This figure is much smaller than the one needed to make
stationary Vlasov-Poisson solver converge in previous studies. Therefore, a population
of trapped electrons seems to be a fundamental component of the expansion but it is
not as large as considered earlier. This is one of the most important conclusions of this
work. Moreover, it has been shown that the exact amount of trapped electrons depends
on the particular history of the system and several steady states are possible.
The model of our work is restricted to the the paraxial and fully magnetized limit
and therefore describes entirely the beam behavior at the axis of the nozzle only. These
and other hypotheses are now revisited. Once the external magnetic field is fixed, the
paraxial approximation adopted in this model, i.e. RL>> R0, imposes a constraint
to the radius R0of the hole at the plasma-vacuum wall. Due to the divergence of the
nozzle, it also limits the maximum axial distance that is meaningful in the numerical
simulations. For a given magnetic field geometry, an estimation of such a distance can be
found by computing the axial position where a magnetic line turns back. The paraxial
hypothesis could be removed from the model by modifying the code slightly: Eq. 6
could be solved for many field lines and Eq. 8should be extended to two-dimensional
(rand z) geometries. On the other hand, at some distance downstream, the local ion
Larmor radius will become comparable to the jet radius and the ions will no longer be
magnetized. Unlike its extension to two-dimensional geometries, the incorporation of
de-magnetization effects to the code, which would involve transport of particles across
different field lines, would not be straightforward.
As presently formulated, the code captures the adiabatic trapping of some electrons
during the initial transient that leads to the development of a fully magnetized expansion
to vacuum. Collisions are entirely neglected in this version, which is appropriate for the
short time scale considered. However, this leaves open the question as to the ultimate
steady state of the trapped electron population over the time scale of many collision
times. The extension of the code to such scenario would require the computation at
each time and location of the multiple integrals over velocities involved in the Boltzmann
collision operator. Since for the usual weak collisionality case the new term will only be
noticeable for times much longer than the initial transient time, it may be appropriate
to neglect collisions until a reasonable steady state is reached and only then to turn
collisions on and allow the gradual relaxation to the final steady state. This extension
of the code would be an important contribution. It could clarify whether or not collisions
erase completely the information about the transient, and if all the possible steady states
of collisionless expansions collapse to a unique state.
G.S-A was supported by the Ministerio de Econom´ıa y Competitividad of Spain (Grant
RYC-2014-15357). J.Z. was supported by Airbus DS (Grant CW240050). J.R. and
M.M-S stays at UC3M for this research were supported by a UC3M-Santander Chair of
Excellence and by National R&D Plan (Grant ESP2016-75887), respectively. E.A. was
supported by the MINOTOR project, that received funding from the European Unions
Horizon 2020 research and innovation programme, under grant agreement 730028.
Appendix A. Description of the numerical scheme
The discretization in velocity space was carried out with Nvk×Nµpoints uniformly
distributed as (vα
max + 2(j1)vα
max/(Nvk1) and µα
k= (k1)µα
with j= 1 . . . Nvkand k= 1 . . . Nµ). The values of vα
max and µα
max, which control the
maximum ranges of the velocity mesh, depend on the specie and were chosen such that
kmax)2=Cvkδα, µα
max ˜
B(z0) = Cµδα,(A.1)
with Cvkand Cµtwo constants. In our simulations we set Cvk= 12.5 and Cµ= 8.95,
which was shown to be large enough (the value of the distribution functions were
negligible close to the boundaries of the velocity mesh).
The distribution function ¯
fα(tm, zi, vα
k) at time tmwas propagated to time
tm+1 =tm+ ∆twith the splitting-time algorithm introduced Ref. [26]. It involves
the following steps (the variable µkis omitted for brevity )
(i) Perform a half time step shift along the z-axis, ¯
α(z, vk) = ¯
fα(tm, z vkt/2, vk).
(ii) Compute the acceleration aα(z, tm+ ∆t/2) by using ¯
αin 7and 8.
(iii) Perform a shift along the vk-axis, ¯
α(z, vk) = ¯
αz, vkaαt
(iv) Perform a half time step shift along the z-axis, ¯
fα(t+∆t, z, vk) = ¯
α(zvkt/2, vk).
A key component of the code is the interpolation scheme, which is needed to
make the shifts along zand vk. After several tests monitoring the conservation of
mass, momentum, and energy by using 11-13 and the results provided by the code, a
cubic interpolation scheme for the z-shifts was selected. For electrons, vk-shifts were
carried out with cubic splines, unless such operation is carried out at the three cells
that adjoin the entrance and the exit of the simulation domain. For these cases, where
the distribution function can be discontinuous due to the imposed boundary conditions,
we used linear interpolation. The filamentation of the electron distribution function
was avoided with the Fourier filter explained in [26]. For ions, spline interpolation in
vkdoes not produce very accurate results due to the discontinuous character of the
distribution function (note that no injected ions come back to the nozzle entrance).
Linear interpolation for the vkinterpolation of the ions gives more accurate results and
was finally used in the simulations. The integrals in velocity space of the distribution
functions, such us nαin 9, were carried out with a Sympson method. The two integrals
in real space appearing in 8were solved with a trapezoidal method.
The code was implemented with OpenMP (shared memory) in Fortran and the
parallel computation took advantage of the conservation of µ. The time propagation
of a piece of the distribution function with a certain µ-range was assigned to a specific
Appendix B. Effect of the convergent segment
Although this work is focused on the divergent segment of the nozzle, we here explain
briefly why it is convenient to add a small convergent segment in the simulation domain,
and the impact of its length, |z0|, in the results of the expansion in the divergent region.
A short parametric analysis for z0=50,25,12.5 and rL= 50, is presented next.
Panel (a) of Fig. B1 displays the normalized charge density profiles in stationary
conditions. The sheath forms always at the left edge of the simulation box and its
strength mitigates as the length of the convergent segment is increased [see inset in
panel (a)]. Eventually the sheath would disappears if the whole plasma source were
included, as it is the case in the stationary model of Ref. [19]. Panels (a) and (b)
show that both the charge density and the electric potential (when referenced to the
throat) are almost unaltered by the segment length (if this is larger than a few Debye
lenghts). The same conclusion was reached for other plasma properties in the divergent
nozzle, like for instance the temperature profiles. In this respect, the results of our
work are robust. If the left edge of the simulation were placed at the throat, a non-
negligible sheath would appear next to the throat affecting significantly the potential
fall along the divergent nozzle. It is clear that there are distribution functions that avoid
the development of a sheath at the left edge, but we do not see a way to characterize
them. The presence of this spurious sheath has been reported also in full particle-in-cell
simulations of unmagnetized and magnetized plumes too [27, 28]
0 200 400 600 800
-40 -20 0 15
0 200 400 600 800
Figure B1. Panels (a) and (b) show the charge densities and potential profiles for
simulations with lengths of the convergent segment equal to z0=50 (solid black),
z0=25 (dashed blue) and z0=12.5 (red dashed-dotted). The curves practically
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... Sánchez-Arriaga et al. [25] have developed a time-dependent, Vlasov-Poisson model for a paraxial MN in an attempt to characterize correctly the subpopulation of trapped electrons. The resulting Eulerian code, named VLAsov Simulator for MAgnetic Nozzles (VLASMAN), determines consistently the subpopulation of trapped electrons generated during the MN start-up transient. ...
... with ǫ 0 the vacuum permittivity, and the condition AB = const was applied. The collisionless case of this model was used in the study of Ref. [25]. A c c e p t e d M a n u s c r i p t ...
... The solutions of the Boltzmann-Poisson model are found with VLASMAN. A detailed explanation of the numerical scheme without collisions is in Ref. [25] and the implementation of the novel collision operator is described in Appendix A. A c c e p t e d M a n u s c r i p t Variables are non-dimensionalized with n 0 , T e0 , λ De0 = ǫ 0 T e0 /n 0 e 2 and c e0 = T e0 /m e . Dimensionless variables are represented with hat on the top: ...
... It is shown later that that the collective MME on a given species appears as the volumetric force n(T ⊥ − T )d ln B/dz in its momentum equation, so a collective MME is closely related to the development of temperature anisotropy. Therefore, Several works on kinetic models consider the plasma expansion in a divergent MN only, placing the plasma source at the throat M (or nearby) [26,110]. This configuration makes full sense when plasma processes on the convergent MN are dominated by phenomena different from magnetic guiding, such as plasma production and heating or interaction with chamber walls. ...
... this scenario, a population of doubly-trapped electrons bouncing between two locations of the magnetic nozzle can exist due to the combination of magnetic mirroring and electrostatic barriers [110,70]. The emergence of empty regions in the electron velocity phase space results in an effective electron cooling [83,95], which indeed leads to an anomalous closure for the fluid equation hierarchy. ...
... Third, the electron temperature at the source is assumed isotropic, which is not the situation expected in an ECR thruster. Theoretical work is underway to cancel or at least reduce these model restrictions[44,110,95,106] Plasma beam characterization along the magnetic nozzle of an ECR thruster3.4.2 Fitting of experimental data along the MN of thePM thrusterThe experimental results for the PM thruster presented in Section 3.3 are here fitted to the model just described. For a given mass flow, the fitting method is applied to the ion velocity profile experimental data ofFigure 3.8 (a) and consists in the following. ...
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This Thesis presents an experimental and theoretical investigation of the fundamental physical phenomena behind magnetic nozzle expansions. The work is motivated by the emerging electric propulsion thruster concepts which include magnetic nozzles to confine and accelerate the plasma beam. This research has been carried out under a bilateral agreement between the Office National d’Etudes et de Recherches Aérospatiales and the Electric Propulsion and Plasma Team from the University Carlos III de Madrid.The first part of this research constitutes an experimental investigation of an Electron Cyclotron Resonance thruster. An innovative procedure based on the integration of a diamagnetic loop signal at the thruster shutdown for estimating the mean perpendicular electron pressure inside the thruster source is presented. The signal is then used to estimate the mean perpendicular electron temperature by means of 1D and 2D theoretical models. Results fairly agree with the direct magnetic thrust measurements of a previous experiment.The magnetic nozzle of the thruster is characterized by means of electrostatic probes and lased induced fluorescence diagnostics. Profiles for the ambipolar plasma potential, ion velocity, plasma density and electron temperature are obtained as a function of the propellant mass flow rate. By combining Langmuir probes with the optical set-up, complete profiles (from the thruster source exit to far downstream) of the ambipolar plasma potential are obtained, which allows to estimate the totalpotential drop along the magnetic nozzle. Different effective electron cooling rates are measured along the expansion for the thruster operating with permanent magnets and for the one with solenoids, which is linked to the different magnetic nozzle topologies. The experimental data is compared with a paraxial steady-state model, showing a good correlation with respect the plasma potential, ion velocity and plasma density. The comparison between the experimental data with the model allows to estimate the sonic transition of the plasma flow, which appears to be shifted from the magnetic throat. A recent publication from another research group verifies our results.The second part of this Thesis presents a theoretical investigation of the ion and electron thermodynamics along the magnetic nozzle expansion. A collisionless, paraxial, steady-state kinetic model is used to investigate in several directions:first, the macroscopic effect of the kinetic aspects along the expansion is discussed. Electrons are barely affected by magnetic mirroring, since anisotropy is only developed very far downstream. On the contrary, magnetic mirror is dominant for ions, especially in the “hot” ions limit. Parametric laws for the downstream properties are given, which can provide a quick estimate of the nozzle performance.The electron distribution function at the upstream source is formulated different from Maxwellian. The case of two electron populations with disparate temperatures is presented, where the kinetic features of a quasi-neutral steepened layer are addressed. The total potential drop of the nozzle is a function of the density fraction of hot electrons and their temperature, and it determines the level of anisotropy of this population.Finally, the electron distribution function at the upstream source is formulated as a bi-Maxwellian anisotropic function. The plasma response along the expansion is investigated in a convergent-divergent nozzle and in a fully divergent one. Strong potential and density gradients are developed as a consequence of expanding a species with a non-isotropic pressure tensor. The gradients sign depends on the convergent/divergent character of the nozzle and on the type of anisotropy.
... Grid-based Eulerian Vlasov and gyrokinetic solvers have been used to study many relevant scenarios in plasma physics, like laser-plasma interaction [1,2], plasma instabilities [3,4], plasma sheaths [5], magnetic nozzles [6], Landau damping [7], and tokamak plasmas [8] (find reviews in Refs [9,10]). As opposed to particle methods, Eulerian solvers avoid the (macro-) particle noise by discretizing the distribution function in phase space. ...
... For instance, a plasma expansion in a slender magnetic nozzle exhibits this problem and, only after adding a heuristic population of trapped electrons, numerical solutions were found [35]. A later study with a non-stationary Vlasov solver showed that there are indeed trapped electrons [6], but they represent a much smaller fraction to the one considered in the stationary analysis. ...
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Physical and numerical limitations of stationary Vlasov-Poisson solvers based on backward Liouville methods are investigated with five solvers that combine different meshes, numerical integrators, and electric field interpolation schemes. Since some of the limitations arise when moving from an inte-grable to a non-integrable configuration, an elliptical Langmuir probe immersed in a Maxwellian plasma was considered and the eccentricity (e p) of its cross-section used as integrability-breaking parameter. In the cylindrical case, e p = 0, the energy and angular momentum are both conserved. The trajectories of the charged particles are regular and the boundaries that separate trapped from non-trapped particles in phase space are smooth curves. However, their computation has to be done carefully because, albeit small, the intrinsic numerical errors of some solvers break these conservation laws. It is shown that an optimum exists for the number of loops around the probe that the solvers need to classify a particle trajectory as trapped. For e p 0, the angular momentum is not conserved and particle dynamics in phase space is a mix of regular and chaotic orbits. The distribution function is filamented and the boundaries that separate trapped from non-trapped particles in phase space have a fractal geometry. The results were used to make a list of recommendations for the practical implementation of stationary Vlasov-Poisson solvers in a wide range of physical scenarios.
... 335,336 These regions would become populated during the transient period of formation of the MN and by sporadic collisions. 367,368 If the repopulation is large, doubly trapped electrons can be the main electron subpopulation in certain MN regions and shape the plasma expansion there. ...
... Since the response of confined electrons is nonlocal, 332,333,382 the definition of consistent downstream (and lateral) boundary conditions is a challenging problem, not fully solved and shared again by magnetized and unmagnetized plumes. 367,398 On the innovation field, first, the development of practical realizations of 3D MNs in order to test and quantify their beam steering capabilities is pending. Indeed, these are very interesting devices to study magnetic confinement in open plasmas and raise novel questions such as the possible distortion of the previous azimuthal loops of electron current into nonclosed streamlines and its effect in confinement. ...
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This paper provides perspectives on recent progress in understanding the physics of devices in which the external magnetic field is applied perpendicular to the discharge current. This configuration generates a strong electric field that acts to accelerate ions. The many applications of this set up include generation of thrust for spacecraft propulsion and separation of species in plasma mass separation devices. These “E × B” plasmas are subject to plasma–wall interaction effects and to various micro- and macroinstabilities. In many devices we also observe the emergence of anomalous transport. This perspective presents the current understanding of the physics of these phenomena and state-of-the-art computational results, identifies critical questions, and suggests directions for future research.
... where the first term completes the circuit and the second enforces the quasi-neutrality. This condition guarantees that quasi-neutrality and current-free conditions are respected at the steady-state, comparable to the algorithms used previously in references [34,36,56]. A similar control strategy has not been imposed to ions since I i * ≡ I i0 ≡ I + i0 , whereas I e * ≡ I + e0 = I e0 . ...
A self-consistent model is presented for performing steady-state fully kinetic Particle-in-Cell simulations of magnetised plasma plumes. An energy-based electron reflection prevents the numerical pump instability associated with a typical open-outflow boundary, and is shown to be sufficiently general that both the plume kinetics and plasma potential demonstrate domain independence (within 4%). This is upheld by non-stationary Robin-type boundary conditions on the Poisson's equation, coupled to a capacitive circuit that allows physical evolution of the downstream potential drop in the transient. The method has been validated against experiments, providing results that fall within the uncertainty of measurements. Simulations are then carried out to study collisional xenon discharges into axisymmetric diverging magnetic nozzles. Particular discussion is given to the identification of a collision-enhanced potential well arising from charge separation at the plume periphery, the role of ion-neutral charge exchange, and a three-region piecewise polytropic cooling regime for electrons. The polytropic index is shown to depend on the degree of magnetisation. Specifically, in the region near the thruster outlet, the plume is weakly-magnetised due to the cross-field diffusion of electron-heavy particle collisions. Downstream, a strongly-magnetised region of near-isothermal expansion occurs. Finally, in the detached region, the polytropic index tends to that of a more adiabatic unmagnetised case. With an increasing magnetic nozzle field strength, an inferior limit is found to the average polytropic index of γ e ∼ 1.16.
... In previous particle simulations of two-dimensional plume expansion, a specific injection scheme is designed to make sure that n e = n i and J i = J e at the injection surface plane. Due to the high mobility of the electrons, the number density of the injected plasma need to be adjust based on the quasi-neutral condition at the injection surface [37][38][39]. With the insights from the particle methods' injection schemes, the following injection scheme (boundary condition at the injection surface) is applied here ...
Conference Paper
View Video Presentation: We present the development progress of a parallel, multi-dimensional grid-based Vlasov solver, Vlasolver. The Vlasov equation is solved using the third order Positive Flux Conservation (PFC) scheme, and the parallelization of the code is implemented using domain decomposition and MPI. The capability of Vlasolver is demonstrated by an application in 2-dimensional plasma plume expansion. We find that the grid-based Vlasov method is advantageous over particle-based methods as it eliminates the inherent statistical noise in particle-based methods in the low density region.
... Instead, the acceleration and detachment phenomena [16] take place downstream the plasma source in the region identified as the acceleration stage (see Figure 1). The latter is characterised by the formation of a plume where the plasma is more rarefied (density in the range 10 16 -10 18 m -3 ) than in the production stage [17]. Particle collisions and the geometry of the applied magnetostatic field govern the plasma behaviour in the region near to the thruster [18]. ...
Conference Paper
Over the last few years, several new space systems relying on plasma propulsion have been proposed. One of the most promising technologies are Magnetically Enhanced Plasma Thrusters (MEPTs). The main components are (i) a dielectric tube, inside which plasma is produced, (ii) a radiofrequency (RF) antenna, dedicated to plasma production and heating, and (iii) solenoids or permanent magnets. The latter generates a magnetostatic field which enhances plasma production and improves the thrust via the magnetic nozzle effect. Consequently, the architecture of a MEPT is extremely simple and low-cost. No electrodes in contact with the plasma or neutralisers are needed, so a MEPT is a long-life device that can be easily operated with different propellants. The MEPT will be demonstrated in orbit in Q1 2021, with the REGULUS propulsion unit for CubeSats from Technology for Propulsion and Innovation SpA (T4i). Despite the simple hardware, the plasma dynamics in a MEPT are non-trivial. The principal phenomena which drive the performance of MEPTs are: (i) Electromagnetic (EM) power deposition in the source, (ii) plasma generation and heating, and (iii) conversion of plasma thermal energy into acceleration by means of the magnetic nozzle. Although semi-analytical models have been developed to estimate the performance of MEPTs, accurate numerical models for the detailed design are still in progress. Each of the three phenomena need to be simulated with a dedicated strategy, to prevent the excessive computational burden associated to multi-scale mechanisms. This work presents a numerical suite targeted at MEPTs that has been developed in the frame of a collaboration between the University of Padova, T4i, and the University of Bologna. The EM problem is solved by means of the well-established 3D solver ADAMANT. The plasma production in the source is handled with the 3D-VIRTUS code that relies on a fluid model. The plasma expansion in the magnetic nozzle is simulated with a fully kinetic Particle-In-Cell approach; both a 3D and a 2D solver (SPIS and Starfish respectively) are available. The mutual interactions between solvers will be discussed, and a comparison between different methods as well as benchmarking of the results against experiments will be presented. Thus the reliability of the numerical suite will be evaluated for the first time. This powerful tool will aid the optimisation of MEPTs and, in turn, will contribute to increasing their widespread application on space missions, in particular on the CubeSat segment.
... In previous particle simulations of two-dimensional plume expansion [26][27][28], a specific injection scheme is designed to make sure thatñ e =ñ i andJ i =J e at the beam exit surface. Due to the high mobility of the electrons, the number density of the injected plasma need to be adjust based on the quasi-neutral condition at the injection surface [29][30][31]. With the insights from the particle methods' injection schemes, the following injection scheme (boundary condition at the injection surface) is applied herẽ ...
Conference Paper
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We present a parallel, multi-dimensional grid-based Vlasov solver (Vlasolver) for plasma plume simulations. The Vlasov-Poisson system is solved using the third order Positive Flux Conservation (PFC) scheme and the parallelization of the code is implemented using domain decomposition and MPI. We find that the grid-based Vlasov method is advantageous over particle-based methods in the low-density plume region because it eliminates the inherent statistical noise in particle-based methods and allows us to extend the solution beyond the self-similar expansion region.
This work focuses on a numerical suite targeted at cathodeless plasma thrusters. A Global Model is used for preliminary estimation of the propulsive performance. In the plasma source, the code 3D-VIRTUS solves self-consistently plasma transport with a fluid approach, including the electromagnetic wave propagation. Starfish and SPIS are used to handle the magnetic nozzle region via a fully kinetic Particle-in-Cell (PIC) model. Starfish solves the plasma dynamics in a two-dimensional axisymmetric domain and has been coupled to 3D-VIRTUS in order to estimate the propulsive performance. SPIS is a three-dimensional PIC code that has been used to simulate the mutual interactions between the satellite surfaces, the propulsion system plumes and the environmental plasma. Results have been benchmarked against thrust measurements performed on a low-power (50 W range) Helicon Plasma Thruster.
A kinetic-electron, fluid-ion model is used to study the 2D plasma expansion in an axisymmetric magnetic nozzle in the fully-magnetized, cold-ion, collisionless limit. Electrons are found to be subdivided into free, reflected, and doubly-trapped sub-populations. The net charge current and the electrostatic potential fall on each magnetic line are related by the kinetic electron response, and together with the initial profiles of electrostatic potential and electron temperature, determine the electron thermodynamics in the expansion. Results include the evolution of the density, temperature, and anisotropy ratio of each electron sub-population. The different contributions of ions and electrons to the generation of magnetic thrust are analyzed for upstream conditions representative of different thruster types. Equivalent polytropic models with the same total potential fall are seen to result in a slower expansion rate, and therefore to underpredict thrust generated up to a fixed section of the magnetic nozzle.
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This paper presents a fully kinetic particle particle-in-cell simulation study on the emission of a collisionless plasma plume consisting of cold beam ions and thermal electrons. Results are presented for both the two-dimensional macroscopic plume structure and the microscopic electron kinetic characteristics. We find that the macroscopic plume structure exhibits several distinctive regions, including an undisturbed core region, an electron cooling expansion region, and an electron isothermal expansion region. The properties of each region are determined by microscopic electron kinetic characteristics. The division between the undisturbed region and the cooling expansion region approximately matches the Mach line generated at the edge of the emission surface, and that between the cooling expansion region and the isothermal expansion region approximately matches the potential well established in the beam. The interactions between electrons and the potential well lead to a new, near-equilibrium state different from the initial distribution for the electrons in the isothermal expansion region. The electron kinetic characteristics in the plume are also very anisotropic. As the electron expansion process is mostly non-equilibrium and anisotropic, the commonly used assumption that the electrons in a collisionless, mesothermal plasma plume may be treated as a single equilibrium fluid in general is not valid.
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The steady, collisionless, slender flow of a magnetized plasma into a surrounding vacuum is considered. The ion component is modeled as mono-energetic, while electrons are assumed Maxwellian upstream. The magnetic field has a convergent-divergent geometry, and attention is restricted to its paraxial region, so that 2D and drift effects are ignored. By using the conservation of energy and magnetic moment of particles and the quasi-neutrality condition, the ambipolar electric field and the distribution functions of both species are calculated self-consistently, paying attention to the existence of effective potential barriers associated to magnetic mirroring. The solution is used to find the total potential drop for a set of upstream conditions, plus the axial evolution of various moments of interest (density, temperatures, and heat fluxes). The results illuminate the behavior of magnetic nozzles, plasma jets, and other configurations of interest, showing, in particular, in the divergent plasma the collisionless cooling of electrons, and the generation of collisionless electron heat fluxes.
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Fast ignition (FI) is investigated via integrated particle-in-cell simulation including both generation and transport of fast electrons, where petawatt ignition lasers of 2 ps and compressed targets of a peak density of 300 g cm −3 and areal density of 0.49 g cm −2 at the core are taken. When a 20 MG static magnetic field is imposed across a conventional cone-free target, the energy coupling from the laser to the core is enhanced by sevenfold and reaches 14%. This value even exceeds that obtained using a cone-inserted target, suggesting that the magnetically assisted scheme may be a viable alternative for FI. With this scheme, it is demonstrated that two counterpropagating, 6 ps, 6 kJ lasers along the magnetic field transfer 12% of their energy to the core, which is then heated to 3 keV.
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Current collection by positively polarized cylindrical Langmuir probes immersed in flowing plasmas is analyzed using a non-stationary direct Vlasov-Poisson code. A detailed description of plasma density spatial structure as a function of the probe-to-plasma relative velocity U is presented. Within the considered parametric domain, the well-known electron density maximum close to the probe is weakly affected by U. However, in the probe wake side, the electron density minimum becomes deeper as U increases and a rarified plasma region appears. Sheath radius is larger at the wake than at the front side. Electron and ion distribution functions show specific features that are the signature of probe motion. In particular, the ion distribution function at the probe front side exhibits a filament with positive radial velocity. It corresponds to a population of rammed ions that were reflected by the electric field close to the positively biased probe. Numerical simulations reveal that two populations of trapped electrons exist: one orbiting around the probe and the other with trajectories confined at the probe front side. The latter helps to neutralize the reflected ions, thus explaining a paradox in past probe theory.
Conference Paper
An electrostatic, full-PIC code is used to study the expansion into vacuum of a 2D plasma plume. The paper first discusses the proper choice of boundary conditions for the particles and electric potential in the simulation domain to avoid or mitigate numerical artifacts. The PIC code is then used to investigate the transition from unmagnetized electrons, as in the plume of a gridded ion thruster, to magnetized electrons, as in a magnetic nozzle.
The azimuthal plasma current in a magnetic nozzle of a radiofrequency plasma thruster is experimentally identified by measuring the plasma-induced magnetic field. The axial plasma momentum increases over about 20 cm downstream of the thruster exit due to the Lorentz force arising from the azimuthal current. The measured current shows that the azimuthal current is given by the sum of the electron diamagnetic drift and E x B drift currents, where the latter component decreases with an increase in the magnetic field strength; hence the azimuthal current approaches the electron diamagnetic drift one for the strong magnetic field. The Lorentz force calculated from the measured azimuthal plasma current and the radial magnetic field is smaller than the directly measured force exerted to the magnetic field, which indicates the existence of a non-negligible Lorentz force in the source tube.
A two-fluid, two-dimensional model of the plasma expansion in a divergent magnetic nozzle is used to investigate the effect of the plasma-induced magnetic field on the acceleration and divergence of the plasma jet self-consistently. The induced field is diamagnetic and opposes the applied one, increasing the divergence of the magnetic nozzle and weakening its strength. This has a direct impact on the propulsive performance of the device, the demagnetization and detachment of the plasma, and can lead to the appearance of zero-field points and separatrix surfaces downstream. In contrast, the azimuthal induced field, albeit non-zero, is small in all cases of practical interest.
The normal magnetic field configuration of a Q device has been modified to obtain a “magnetic Laval nozzle.” Continuous supersonic plasma “winds” are obtained with March numbers ∼3 . The magnetic nozzle appears well suited for the study of the interaction of supersonic plasma “winds” with either material or magnetic obstacles.
Plasma detachment in propulsive magnetic nozzles is shown to be a robust phenomenon caused by the inability of the internal electric fields to bend most of the supersonic ions along the magnetic streamtubes. As a result, the plasma momentum is effectively ejected to produce thrust, and only a marginal fraction of the beam mass flows back. Detachment takes place even if quasineutrality holds everywhere and electrons are fully magnetized, and is intimately linked to the formation of local electric currents. The divergence angle of the 95%-mass flow tube is used as a quantitative detachment performance figure.
Using laser-induced fluorescence, measurements have been made of metastable argon-ion, Ar+*(3d4F7/2), velocity distributions on the major axis of an axisymmetric magnetic-mirror device whose plasma is sustained by helicon wave absorption. Within the mirror, these ions have sub-eV temperature and, at most, a subthermal axial drift. In the region outside the mirror coils, conditions are found where these ions have a field-parallel velocity above the acoustic speed, to an axial energy of ~30 eV, while the field-parallel ion temperature remains low. The supersonic Ar+*(3d4F7/2) are accelerated to one-third of their final energy within a short region in the plasma column, <=1 cm, and continue to accelerate over the next 5 cm. Neutral-gas density strongly affects the supersonic Ar+*(3d4F7/2) density.