1. Introduction
Numerical simulations of flows in the transition from the gas kinetic (mesoscopic) to the fluid dynamic regime (macroscopic) represent a demanding task. On the mesoscopic side, the collision term operates on the six-dimensional phase space and is very complex. On the macroscopic side, including a collision term in the fluid dynamic equations makes the problem become numerically stiff and hard to resolve in time.
In this situation, simplifying models are en vogue. The most popular ones are systems of BGK type (
Bhatnagar–Gross–Krook models, see [
1]) which treat mesoscopic effects applying simple one- or more-parameter relaxation rules. Theoretical models try to find formulas from asymptotic analysis, taking into account the small mesoscopic perturbations as terms of an expansion with respect to some small parameter
(Hilbert, Chapman–Enskog expansion). From this, we find the Euler and the Navier Stokes equations as zeroth and first order approximations. Improved models, e.g., for a more detailed refinement of the pressure tensor are expected from higher order terms.
In the course of the present paper we demonstrate that all these models fail in certain practically relevant situations. E.g., the
-expansion ansatz fails in some condensation-evaporation problems for a gas mixture (see
Section 6.2), leading to some unphysical
ghost effects. The BGK ansatz yields systematic errors even in simple heat layer problems (
Section 6.1). In the following, we propose new ansatz (
trace solutions) which works on the tangent space to the set of all Maxwellians (rather than the classical ansatz
“solution = Maxwellian plus orthogonal perturbation”, supplemented with an exponential relaxation rule). As a motivation, we discuss the relaxation of a simple local perturbation problem (see
Section 5.2). The crucial feature of the new approach is that (close to the fluid dynamic limit) the local macroscopic moments are not reflected by the local Maxwellian but by a specific moment perturbation.
The idea to construct intermediate states between arbitrary density functions and Maxwellians is not new. E.g., Shakhov [
2] proposed such a system which is at present used for numerical simulations [
3]. A comparable intention lies behind the idea of the extended BGK model with an additional relaxation parameter to match the correct Prandtl number, or related generalizations [
4]. However, a better understanding of the transfer to fluid dynamics is not a question of parameter matching, and the above approaches do not yield a theoretical basis and a safe mathematical ground. Proposing a modified structure of kinetic solutions, the present paper claims to provide a new attempt to better understand the passage from the rarefied gas description to the macroscopic limit.
We derive closure relations which take the form of nonlinear first order (rather than second order) differential terms and thus are completely different from the parabolic second order terms of the Navier–Stokes system. The results allow one to interpret the differences in various kinetic models (here: nonlinear and linearized Boltzmann collision operators and the BGK relaxation operator) in the fluid dynamical limit. As particular results, we point at a purely nonlinear effect of the Boltzmann collision operator which is not reflected in the Navier–Stokes approach (
Section 5.3), and we demonstrate that the BGK system produces systematic artificial effects which are non-local and which do not vanish in the fluid dynamical limit (
Section 6.1).
The derivation of the trace ansatz requires some tedious mathematical arguments, which are necessary for a sufficient understanding of the mathematical framework. The technical part has been worked out in [
5] (with Lea Bold as coauthor who has contributed the numerical results of
Section 5.3 which are crucial for the justification of the trace ansatz [
6]). In the present paper, we have tried to shift the focus from the technical part to the applications (in particular,
Section 6.2), while keeping the paper self-contained.
Having derived the trace ansatz, we have performed numerical simulation studies for testing and comparing the various models mentioned above. As a numerical tool, we used discrete velocity models (in the version as described in [
7]) on
- and
-velocity grids, respectively, which are sufficient in our cases. These are applicable in identical form for all of the discussed models. (To implement collision terms on grids in an efficient manner with valid flow parameters, the application of computer algebra tools is recommended, as demonstrated in [
8].) These systems are well investigated, with systematic errors in numerical simulations being well understood and under control [
9]. Grids of the above size are preferable mainly for small to moderate Mach numbers, creep flows, etc. The numerical results are in full agreement with the theoretical results.
The paper is organized as follows.
Section 2 gives a short review of the above-mentioned kinetic models.
Section 3 introduces the general (non-closed) moment system derived from gas kinetics and derives the Euler system.
Section 4 reinterprets the steps of the first order Chapman–Enskog approach for the Navier–Stokes system. In this way, the central point of the procedure can be generalized and becomes applicable to the full nonlinear collision operator without recourse to a formal series expansion. A new concept of balanced states is introduced, which are elements of the tangent space to the manifold of the Maxwellians and which replace (respectively, supplement) the first order terms of the density function as provided by the Chapman–Enskog procedure. In
Section 5, we introduce the concept of traces of kinetic solutions. Traces are comparable to projections of kinetic solutions onto the tangent spaces. The differential structure of the underlying dynamics provides a powerful tool to describe distributions in the neighborhood of Maxwellians. In order to keep the underlying ideas as concise and understandable as possible, we restrict theory and numerical example one-dimensional geometries.
Section 6 applies the results to the heat layer problem and discusses an evaporation condensation problem for gas mixtures.
2. Kinetic Models
The most fundamental kinetic model equation for a density function
(
x space-,
velocity parameter) of a single-species gas in phase space
(
) is the classical Boltzmann equation (see, e.g., [
10,
11])
The
Boltzmann collision operator is a bilinear operator integrating over all possible conservative two-particle collisions. It satisfies the conservation laws
The Boltzmann collision operator is ruled by the H-Theorem stating that in a space homogeneous environment all densities converge for
to equilibrium functions
e (these are functions satisfying
); all equilibrium functions are
Maxwellians, i.e., functions of the form
uniquely determined by its macroscopic moments
In the following, we denote by
the space of collision invariants, and by
its orthogonal complement. We make use of the following.
(2.1) Decomposition Lemma: Given a nonnegative density
f and a Maxwellian
e, there exists a unique decomposition
with
M defined as
The decomposition takes the form
iff
e has the same macroscopic moments as
f.
( is a shorthand notation for an element in , fully written as .)
Proof. r can be uniquely determined by calculating mass, momenta and temperature on both sides. □
The set of all Maxwellians is denoted by
. Given
, the
tangent space in
e is defined by
The
full tangent space is the union
Two simplified alternatives to the nonlinear Boltzmann collision operator are the
linearized collision operator and the
BGK relaxation model . Both are based on decomposition (11). Given
, the Boltzmann collision operator is
Dropping the term which is quadratic in
, we end up with the
linearization of around e,
transfers
f exponentially in time to its equilibrium
e. The well-known properties of
are as follows.
(2.2) The linearized collision operator: Write . Then
- (a)
- (b)
K is self-adjoint (e.g., in a weighted space) and negative semidefinite.
- (c)
The restriction has an inverse .
- (d)
The linear system
is solvable iff
. In this case, the solution is
It satisfies
For a more thorough treatment of
, see, e.g., [
10,
12]. For corresponding results in the case of Discrete Velocity Models, see [
7,
13].
The simplest kind of exponential decay of
f to its equilibrium
e is given by the
one-parameter BGK model
The solution of the linear system corresponding to (18) follows immediately from calculation.
(2.3) Linear system for BGK: Suppose
. The unique solution of
is
4. Navier–Stokes Equations and Balanced States
A prominent role in the refinement of the Euler system is played by the solutions
(
),
and
in
of the linear equations (with
)
(For the solvability of the equations, see (2.2)(c).)
A convenient way to derive the Navier–Stokes system is the Chapman–Enskog expansion of first order. We plug the ansatz
into the Boltzmann equation and set equal the terms of equal power of
. For
, we find
and thus
. For
we find
For its solution, we perform decomposition (9) on the whole system. The part acting on
reads
with
The solution of (
40) is
We now obtain the
Navier–Stokes correction to the Euler equations by calculating moment system (3.4) of the function
. Taking into account inequalities (
17), we find the correction terms to the closure moments of the Euler system,
with the positive viscosity and heat coefficients
All the above results are classical and need no further explanation. Here, we find a way to reinterpret the Chapman–Enskog results and to generalize them, without making use of the series expansion.
(4.6) Lemma: Let
be a fixed Maxwellian and
the corresponding flow term. The expansion of first order
of Chapman–Enskog is the unique asymptotic solution (
) of the time-homogeneous initial value problem (IVP)
Proof. Decompose
f uniquely into the form
Since
and
, we find
and
solution of the IVP in
,
Since
is invertible and negative definite, the asymptotics
exists and satisfies
Thus,
□
Thus, the Chapman–Enskog procedure as sketched above may be seen as a special case of the following three-step procedure for the calculation of closure relations.
(4.7) Scheme for closure relations: (1) Let and be given and fixed. Calculate a reduced description of f containing all information concerning the relevant moments.
(2) For an appropriate approximation
C of the Boltzmann collision operator, solve the IVP
(3) Determine and calculate from this the closure relations for f.
(In the Chapman–Enskog case,
and
.) We can interpret (
49) as a local solution to the kinetic equation: Introduce a microscopic time scale
and solve the kinetic system. In lowest order in
, we freeze the source term
at
and solve the system for
. In the following, we call the distributions
balanced states, since they balance the trend to equilibrium given by the collision operator with the perturbing effects produced by the streaming term.
7. Conclusions
In certain situations, it is necessary to put fluid dynamical problems on a safe ground derived from gas kinetic models. In this situation, one ends up with a non-closed moment system of the form (3.4) which has to be supplemented with closure relations for the pressure tensor and the heat flux. We have shown that the most popular models like expansion techniques (Hilbert, Chapman–Enskog) or relaxation systems (BGK or related extensions) fail in certain situations. (See
Section 6.1 for the heat layer problem and
Section 6.2 for an evaporation condensation problem for gas mixtures).
In the present paper, we introduced an alternative approach which avoids mysteries (“ghost effect”) and some of the deficiencies of standard theory. The reason is that the trace ansatz allows portions of the flow to coexist at the same place with different temperatures or bulk velocities. This may be the case, e.g., close to interfaces (outgoing/reflected flows, different species of a mixture etc.). In such situations, our method is superior to the classical schemes. In fact, we do not know of any theoretical ansatz successfully attacking e.g., the evaporation condensation problem in the fluid dynamic limit.