A finite difference method for inhomogeneous incompressible Navier-Stokes equations
Kohei Soga

TL;DR
This paper analyzes a fully discrete finite difference scheme combining explicit and implicit methods for inhomogeneous incompressible Navier-Stokes equations, proving convergence to weak solutions under certain conditions.
Contribution
It introduces a novel convergence proof for a finite difference scheme applied to inhomogeneous Navier-Stokes equations, including a new compactness method.
Findings
Proven strong convergence of the scheme to a weak solution.
Established existence of weak solutions for the inhomogeneous system.
Developed a new Aubin-Lions-Simon type compactness technique.
Abstract
This paper provides mathematical analysis of an elementary fully discrete finite difference method applied to inhomogeneous (non-constant density and viscosity) incompressible Navier-Stokes system on a bounded domain. The proposed method consists of a version of Lax-Friedrichs explicit scheme for the transport equation and a version of Ladyzhenskaya's implicit scheme for the Navier-Stokes equations. Under the condition that the initial density profile is strictly away from , the scheme is proven to be strongly convergent to a weak solution (up to a subsequence) within an arbitrary time interval, which can be seen as a proof of existence of a weak solution to the system. The results contain a new Aubin-Lions-Simon type compactness method with an interpolation inequality between strong norms of the velocity and a weak norm of the product of the density and velocity.
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Taxonomy
TopicsDifferential Equations and Numerical Methods · Numerical methods for differential equations · Advanced Mathematical Modeling in Engineering
A finite difference method for inhomogeneous incompressible Navier-Stokes equations
Kohei Soga 111Department of Mathematics, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Japan. E-mail: [email protected]
Abstract
This paper provides mathematical analysis of an elementary fully discrete finite difference method applied to inhomogeneous (non-constant density and viscosity) incompressible Navier-Stokes system on a bounded domain. The proposed method consists of a version of Lax-Friedrichs explicit scheme for the transport equation and a version of Ladyzhenskaya’s implicit scheme for the Navier-Stokes equations. Under the condition that the initial density profile is strictly away from [math], the scheme is proven to be strongly convergent to a weak solution (up to a subsequence) within an arbitrary time interval, which can be seen as a proof of existence of a weak solution to the system. The results contain a new Aubin-Lions-Simon type compactness method with an interpolation inequality between strong norms of the velocity and a weak norm of the product of the density and velocity.
Keywords: inhomogeneous incompressible Navier-Stokes equations; transport equation; weak solution; finite difference method
AMS subject classifications: 35Q30; 35Q49; 35D30; 65M06
1 Introduction
We consider the inhomogeneous incompressible Navier-Stokes equations on a general bounded domain of , i.e., the standard model of a mixture of miscible incompressible fluids with different densities and the non-constant viscosity,
[TABLE]
where is the unknown velocity, is the unknown density, is the unknown pressure, is a given viscosity function depending on the density, is a given external force, is an arbitrary positive terminal time, and are initial data, , , , , etc., stand for the partial (weak) derivatives of , is the Jacobian matrix of and stands for the transpose of . In this paper, we suppose that , , and are such that
[TABLE]
where does not need to be from . Here, is the family of -functions : that are equivalently [math] near ; ; ; is the closure of with respect to the norm ; (resp. ) is the closure of with respect to the norm (resp. ); , where coincides with provided is Lipschitz (see, e.g., Theorem 1.6 and Remark 1.7 of Chapter 1 in [22]); for .
If and are smooth, the first, second and third equations of (1.8) yield
[TABLE]
This leads to the following definition of a weak solution of (1.8): a pair of functions and is called a weak solution of (1.8), if
[TABLE]
We remark that the choice of in (1) implies that the [math]-extensions of , and outside provide the unique DiPerna-Lions weak solution of (1.9) in obtained in [4]; hence belongs to for all (see Introduction of [20]).
Existence of a weak solution to (1.8) was established by Antontsev-Kazhikhov [1] and Kazhikhov [10] based on a Galerkin method under the assumption that the initial density profile is strictly positive and the viscosity is constant. Then, with finer a priori estimates, Kim [11] and Simon [19] removed the positivity assumption, where the -regularity of the velocity was missing; Lions [16] allowed the non-constant viscosity. We refer to Danchin-Mucha [3] for further developments and reviews of mathematical analysis of (1.8) including its strong solutions.
In regards to mathematical analysis of numerical methods for (1.8), Liu-Walkington [17] proposed a numerical scheme that was strongly convergent to a weak solution based on a discontinuous Galerkin method for (1.9) and a finite element method for (1.10), where they supposed the positivity condition for the density but allowed the non-constant viscosity. Guermond-Salgado [7] demonstrated error analysis of a Galerkin type numerical method applied to (1.8) (with strictly positive density and the constant viscosity coefficient) assuming existence of a smooth solution.
The purpose of this paper is to provides an elementary but rigorous approach to the existence of weak solutions of (1.8) based on a very simple finite difference scheme (we postpone actual implementation of the scheme for numerical tests). We are inspired by a finite difference scheme applied to homogeneous incompressible Navier-Stokes equations, and therefore we give a brief overview of the development of finite difference methods in the homogeneous case. In the huge literature of homogeneous incompressible Navier-Stokes equations, there are a number of results on mathematical analysis of various numerical methods. Among them, finite difference methods seem to be more elementary and direct to the exact differential equations than other major methods. To the best of author’s knowledge, the first rigorous treatment of fully discrete finite difference approximation of the homogeneous incompressible Navier-Stokes equations was given by Krzywicki-Ladyzhenskaya [12] and Ladyzhenskaya [14] (here, we call it Ladyzhenskaya’s scheme), where they proposed an elementary fully discrete implicit finite difference scheme on the uniform Cartesian grid to discretizes the homogeneous Navier-Stokes equations including the pressure and the divergence-free constraint. In [14], she showed its solvability and a priori estimates; although she skipped details of its strong convergence to a Leray-Hopf weak solution, the issue turned out to be rather delicate, i.e., some “equi-continuity” with respect to the time variable or so-called the Aubin-Lions-Simon compactness method is necessary (see, e.g., [15] and [22]). Chorin [2] modified Ladyzhenskaya’s scheme by separating the step of realizing the (discrete) divergence-free constraint from the discrete time evolution, where he demonstrated a convergence proof and error estimates of the scheme assuming a smooth exact solution on a or -dimensional torus. Temam [21] also investigated this type of fully discrete scheme based on a framework of finite element methods. Their methods are nowadays called projection methods and many versions are known. Kuroki-Soga [13] proved convergence of (slightly modified) Chorin’s original scheme to a Leray-Hopf weak solution by adjusting Aubin-Lions-Simon compactness arguments to space-time step functions with the discrete divergence-free constraint and the discrete time-differentiation, where difficulty comes from the fact that the discrete divergence-free constraint and the discrete time-differentiation vary according to the mesh size (one cannot work only within or ).
In this paper, we employ a version of Ladyzhenskaya’s scheme to (1.10), not a projection method. The advantage to do so is that Ladyzhenskaya’s scheme provides a discrete velocity field possessing both the discrete divergence-free constraint and a good (discrete) -bound. Note that Chorin’s scheme does not have such a feature (see [13]). As for (1.9), we use a Lax-Friedrichs type explicit scheme. Our combination of the two schemes, which is probably the simplest method to solve (1.8), must overcome the following difficulties in order to achieve strong convergence to a weak solution:
- (D1)
The velocity field in (1.9) can be unbounded and verification of the CFL-condition for the Lax-Friedrichs explicit scheme is non-trivial. 2. (D2)
Aubin-Lions-Simon type compactness arguments to prove strong convergence of the approximate velocity field refer to its discrete time-derivative, but controllability of the discrete time-derivative of the velocity field through (1.9) is not clear, i.e., what we actually have is the discrete time-derivative of [density][velocity].
An idea to overcome (D1) was given by Soga [20], where he showed a new technique to deal with the transport equation with an unbounded Sobolev velocity field through the Lax-Friedrichs type explicit scheme, introducing the generalized hyperbolic scale (see (3.1) below) and truncation of the velocity field together with a suitable measure estimate for the truncated part. The direct consequence of this method is weak convergence to a DiPerna-Lions weak solution obtained in [4], but a fine estimate of the norm of approximate solutions implies that the weak convergence is in fact strong convergence (it is essential that a DiPerna-Lions weak solution conserves its -norm). We will follow this idea to deal with (1.9), where local averaging of possibly unbounded velocity fields is used instead of the truncation used in [20] in order to keep the discrete divergence-free constraint; an artificial boundary condition is imposed to the discretization of (1.9); the artificial boundary condition does not cause any harm to the solution, if the (locally averaged) velocity field vanishes on the boundary; since the support of the locally averaged velocity field can be slightly larger than , (1.9) will be solved on a domain larger than with constant-extension of the velocity field and the density field.
(D2) will be overcome by modification of the interpolation inequality for the discrete velocity field obtained by Kuroki-Soga [13] in such a way that the “weak norm” of the velocity field is replaced by that of [density][velocity] (see Lemma 4.4 below); this is possible as long as the density is positive almost everywhere. In the end, we will see that the whole reasoning is quite similar to the homogeneous case.
It is an open question how to treat the case with vacuum () in our framework (strong convergence of the approximate velocity field is not clear). It would be also interesting to place our finite difference framework in the context of compressible problems, where we refer to [9], [5], [6] and [8] for recent developments of mathematical analysis of numerical methods for compressible Navier-Stokes equations.
Section 2 provides the notation and basic calculus on the uniform Cartesian grid. Section 3 discusses the unique solvability and a priori estimates of the discrete problem. Section 4 demonstrates convergence of our scheme.
2 Preliminary
Consider the grid with the mesh size . Let be the standard basis of . The boundary of is defined as .
Let be a bounded, open, connected subset of with a Lipschitz boundary . Set
[TABLE]
We discretize (1.10) on the set
[TABLE]
For technical reasons (we will see them later), we solve (1.9) on a domain slightly larger than : let be a connected bounded open set such that
[TABLE]
We discretize (1.9) on the set
[TABLE]
where we always assume that .
Define the discrete derivatives of a function with as
[TABLE]
for each , where we always assume that is extended outside in a certain way, i.e., are given even if ; in particular, if , we take the [math]-extension. For , set , . Define the discrete gradient and the discrete divergence for functions and as
[TABLE]
for each . We often use the summation by parts such as
[TABLE]
for functions that are extended to be [math] outside .
Define the discrete -norms of a function or with as
[TABLE]
in particular for , we introduce the discrete inner product as
[TABLE]
We introduce a local averaging operator , which plays on like the mollifier in . For each , define the set
[TABLE]
For each function or , extend to be [math] outside and define the locally averaged function or as
[TABLE]
where ; in particular and as . An easy calculation shows that
[TABLE]
In fact, the case of is clear; in the case , with , we have by Hölder’s inequality,
[TABLE]
For a technical reason (we will see it later), we sometimes need to argue in an inner part of . Define
[TABLE]
When the central difference is used, we must look at the -translation invariant subsets of the grid , i.e., are the sets of grid points with index even, even, even, even, even, odd, even, odd, even, odd, even, even, even, odd, odd, odd, odd, even, odd, even, odd, odd, odd, odd, respectively. In particular, the [math]-mean value condition of to verify is given on each . We always assume that is small enough so that is connected, i.e., for any , we have such that for all and . We state a discrete Poincaré type inequality:
Lemma 2.1** (Lemma 2.3 of [18]).**
There exists a constant depending only on for which each function satisfies
[TABLE]
The reason why we use is to avoid the presence of the values of on ; see the upcoming application of the lemma to the discrete pressure, where the value of its discrete -derivative on is out of any estimate.
In order to take out the discrete divergence-free part of initial data, we need the discrete Helmholtz-Hodge decomposition with the central difference:
Lemma 2.2** (Theorem 2.4 of [18]).**
For each function , there exist unique functions and such that
[TABLE]
The discrete Helmholtz-Hodge decomposition operator for each function is defined as
[TABLE]
We state a Korn type inequality.
Lemma 2.3**.**
For each function such that with the [math]-extension outside , it holds that
[TABLE]
Proof.
The assertion follows from
[TABLE]
∎
3 Discrete problem
Let be a mesh size for time and let be the discrete terminal time, i.e., . We sometimes use the notation for . Throughout this paper, we suppose the following generalized hyperbolic scaling condition for the mesh size :
[TABLE]
Note that the necessity of the generalized hyperbolic scaling condition comes only from the explicit scheme for (1.9); closer to would cause less numerical diffusivity; will be the order of truncation of the possibly -unbounded discrete velocity fields so that the CFL-condition is valid, where truncation is done by the local averaging ; closer to would require larger , which could increase the truncation error.
Let be a given external force and let and be initial data of (1.8) satisfying
[TABLE]
We extend to as
[TABLE]
Define with , , and as
[TABLE]
where is chosen in the following manner:
[TABLE]
Note that on due to (see (2.1)).
We introduce our discrete problem, which is a system of explicit-implicit recurrence equations. For given and with on and on (if , the conditions on and on are not required), we want to obtain , and through the following discrete system:
[TABLE]
Here are several remarks on the discrete problem:
- •
\displaystyle\quad D\cdot(\eta^{n}\tilde{u}^{n})(x)=\sum_{j=1}^{3}\frac{1}{2h}\Big{(}\eta^{n}(x+he^{j})\tilde{u}^{n}_{j}(x+he^{j})-\eta^{n}(x-he^{j})\tilde{u}^{n}_{j}(x-he^{j})\Big{)},
[TABLE]
- •
Even if , we have in general; if we consider (3.6) on , the norm of is not controlled properly due to the effect of ; we will see later that for all sufficiently small , which provides a good control of the norm of and consequently its strong convergence.
- •
If () satisfies on and on , we have on .
- •
The form of the discrete -derivative in (3.6) is necessary for the CFL-condition to be fulfilled.
- •
The same form of the discrete -derivative is required in (3.8) for consistency in energy estimates (the energy inequality must contain the terms exactly the same as the left hand side of (3.6) for cancelation).
- •
The second and third terms in the left hand side of (3.8) are corresponding to .
- •
is necessary to verify (3.10), where additional conditions for the mean value of is necessary to obtain uniquely.
- •
(3.8) is a version of Ladyzhenskaya’s discrete scheme for the homogeneous incompressible Navier-Stokes equations [12], [14], where it is designed so that the nonlinear term has null-contribution in -estimates.
3.1 Unique solvability
We prove the unique solvability of our discrete problem. For this purpose, we impose the [math]-mean value condition on over for each .
Proposition 3.1**.**
For given with and with on and on (if , the conditions on and on are not required), there exist with , and that solve (3.6)-(3.10); and are unique, while is unique up to its mean value over .
Proof.
It is clear that is uniquely obtained by (3.6) and (3.7). In order to check , rewrite (3.6) as
[TABLE]
Due to the scale condition (3.1), the bound of and the discrete divergence-free constraint of , we have
[TABLE]
Hence, if , we have . This reasoning works also for due to the definition of initial data.
We discuss the unique existence of and . Our argument will also show how to construct and . Suppose the [math]-mean value condition of :
[TABLE]
We note that any function with satisfies
[TABLE]
due to cancelation. We label each point of and as
[TABLE]
Set and as
[TABLE]
where has zeros coming from (3.10) in front of . We see that the equations (3.8)-(3.10) and (3.13) are written as a -system of linear equations, which is denoted by with a -matrix . Since (3.9) and (3.10) implies (3.14), we find the eight trivial equalities in . Hence, can be deduced to be of the form with a -matrix and .
Our proof is complete, if is proven to be invertible, i.e., if and only if . We have at least one solution to . Then, we obtain at least one pair satisfying
[TABLE]
Due to the summation by parts, we have
[TABLE]
Similarly, we have
[TABLE]
where we see that (i)(ii) by shifting to in (i), (ii), respectively. Hence, we obtain by (3.15) with (3.16), (3.17) and (3.6),
[TABLE]
which leads to on due to the positivity of , and . Therefore, (3.15) implies on , i.e., is constant on . (3.13) yields on . Thus, we conclude that only admits the trivial solution and is invertible. This reasoning works for as well. ∎
3.2 A priori estimates
We provide -independent estimates for the discrete problems that are required in the convergence proofs given in Section 4. Note that we do not necessarily seek for the sharpest estimates.
Proposition 3.2**.**
The solution of the discrete problem (3.6)-(3.10) satisfies for all ,
[TABLE]
Proof.
We already proved the first inequality of (3.19) in the proof of Proposition 3.1; the second one in (3.19) follows from the positivity of . Let be the Hölder conjugate of . Observe that
[TABLE]
Rewrite (3.1) as
[TABLE]
where
[TABLE]
Note that due to (3.12) and . For each , it holds that
[TABLE]
Applying the (discrete) Hölder inequality to the right hand side with respect to , we obtain
[TABLE]
which leads to
[TABLE]
Noting and , we sum up (3.22) over to obtain
[TABLE]
which yields (3.2) for .
We prove (3.2). Since and are non-negative, it follows from the inequality of arithmetic and geometric means that
[TABLE]
By calculations done in the proof of Proposition 3.1, we have
[TABLE]
By the calculation (3.18) and Lemma 2.3, we have
[TABLE]
Hence, (3.8) yields
[TABLE]
where the term is equal to [math] due to (3.6). ∎
Corollary 3.3**.**
The solution of the discrete problem (3.6)-(3.10) satisfies for all ,
[TABLE]
Proof.
It follows from (3.2) and (3.2) that for any ,
[TABLE]
Set for and . Then, we have
[TABLE]
from which we obtain for any ,
[TABLE]
Hence, we have for any ,
[TABLE]
We can directly estimate through (3.2)n=0 as
[TABLE]
Therefore, we conclude that for any ,
[TABLE]
Through (3.2)n=0, we see that
[TABLE]
It follows from (3.2) and (3.2) that for any ,
[TABLE]
∎
Although convergence of is not required, we need some estimates for it in Section 4. Taking the inner product of (3.8)i=1,2,3 and , we have
[TABLE]
By the already obtained estimates and the bound of , we obtain with a -independent constant ,
[TABLE]
This estimate will be used in the following way: for , where is still denoted by and supp for all sufficiently small , it holds that
[TABLE]
due to Lemma 2.1, we have
[TABLE]
4 Convergence
We investigate weak and strong convergence of the solution to the discrete problem. For each , define the step functions , , generated by the solution of (3.6)-(3.10): on ,
[TABLE]
where , and for the value of each step function is defined as the value at . In the rest of our argument, the statement “there exists a sequence …” means “there exists a sequence with as …”.
4.1 Weak convergence
We first investigate weak convergence, which is rather straightforward from the results in Subsection 3.2. The proof requires Lipschitz interpolation of functions defined on :
Lemma 4.1** (Appendix (1) of [13]).**
For a function with and the step function defined as
[TABLE]
there exists a Lipschitz continuous function with supp such that
[TABLE]
where and are constants independent of and .
Proposition 4.2**.**
There exists a sequence and functions , , for which the following weak convergence holds:
[TABLE]
Proof.
Subsection 3.2 shows that , , , () are bounded in the Hilbert space or . Hence, there exists a sequence and functions and such that for ,
[TABLE]
In the rest of the proof, is such that with supp. Set .
We prove . Noting the regularity of , we have for each ,
[TABLE]
Therefore, the weak convergence implies for any .
We prove a.e. . For each , we have
[TABLE]
Therefore, we obtain for any . Up to now, we proved and a.e. .
We prove . Let be the Lipschitz interpolation of by means of Lemma 4.1 and let be defined as for , (). Note that
[TABLE]
for , where is a constant independent from . We see that, taking a subsequence if necessary, in as and that there exists such that in as for . Since for any , we have and . In particular,
[TABLE]
Since is a bounded sequence of the Hilbert space , taking a subsequence if necessary, we find to which weakly converges in as , i.e.,
[TABLE]
Therefore, we have (v-\bar{v},\psi)_{L^{2}([0,T];H^{1}(\Omega)^{3})}=0\mbox{ \,\,\,for any \psi\in L^{2}([0,T];H^{1}_{0}(\Omega)^{3}).} Since , we obtain
[TABLE]
which means that .
Thus, we conclude that . ∎
We show -pointwise weak convergence of , which is required in the next subsection.
Proposition 4.3**.**
There exists a sequence and such that for every ,
[TABLE]
Proof.
We use an Ascoli-Arzela type reasoning. Set . Since is bounded in , there exists a subsequence and such that in as . We check that : set ; since , we have for all and as ; hence and , i.e., ; similarly, set ; since , we have for all and as ; hence and , i.e., .
Since is bounded in , there exists a subsequence and such that in as , where . Repeating this process, we obtain a subsequence and such that in as , where , for each . It is clear that , satisfies
[TABLE]
In order to see weak convergence of for all , we check “equi-continuity” of with respect to for each fixed . Let etc., denote the quantities that generate the step function . There exists such that on for all and for all . If , the solution satisfies
[TABLE]
where with a constant independent from , . Hence, we have
[TABLE]
For any , set so that , and if and if . It follows from (3.23) that there exists a constant independent from , , such that if ,
[TABLE]
which includes the case of because if . Fix an arbitrary small . There exists and such that
[TABLE]
Let . Take a rational number from each , ( if ). For any , there exists such that . Since is s convergent sequence of , there exists such that if we have
[TABLE]
Set as
[TABLE]
Then, we have for any ,
[TABLE]
Therefore, is a convergent sequence of . On the other hand, since is bounded in , we have a subsequence and such that and
[TABLE]
which implies that
[TABLE]
Since is dense in , we conclude that in as for every . ∎
In the rest of paper, , , are the sequences that satisfy the weak convergence shown in Proposition 4.2 and Proposition 4.3.
4.2 Strong convergence of
Our aim is to prove that the pair of and found in Proposition 4.2 is a weak solution of (1.8). For this purpose, we prove -strong convergence of to through the following steps taken in [13], which can be seen as a version of well-known Aubin-Lions-Simon approach:
- (S1)
Suppose that the weakly convergent sequence obtained in Proposition 4.2, which is re-denoted by ( is also re-denoted by ), is not strongly convergent in , i.e., is not a Cauchy sequence in .
- (S2)
Then, there exists such that for each we have for which holds.
- (S3)
We will see that is bounded from the above by two different “norms”.
- (S4)
We are able to estimate the “norms” to tend to [math] as , only with the information on the discrete time-derivative of and weak convergence of , and we reach a contradiction.
As we will see later, once -strong convergence of is proven, we also obtain -strong convergence of to .
The Aubin-Lions lemma (see, e.g., Lemma 2.1 in Section 2 of Chapter III, [22]) is standard in this kind of arguments. Kuroki-Soga [13] modified Aubin-Lions lemma in the convergence proof for Chorin’s projection method applied to the homogeneous incompressible Navier-Stokes equations so that reasoning similar to Aubin-Lions-Simon approach works under the discrete divergence-free constraint that depends on . Here, we further modify Kuroki-Soga’s approach (our current discrete problem provides the solution that is (discrete) -bounded and divergence-free, while Chorin’s projection method provide the solution that is (discrete) -bounded but only “asymptotically” divergence-free).
In the case of constant density problems, the modified Aubin-Lions-Siom approach applied to the sequence refers to the discrete time-derivative of , which is treated with the discrete Navier-Stokes equations. However, in the case of non-constant density problems, the controllable quantity is the discrete time-derivative of . Because of this, we must further modify the Aubin-Lions type interpolation inequality so that the discrete time-derivative of can be involved in the weak norm.
We provide the “norms” mentioned in (S3) and state the interpolation inequality. Let (resp. ), etc., be the quantities that provide the step functions , (resp. , ). For each , take such that , if and if ; define
[TABLE]
where *the supremum is taken over all such that and supp, supp *; means .
Lemma 4.4**.**
For each , there exists independent of such that
[TABLE]
Remark. *The presence of would play an important role when we possibly have , where it is not a priori clear or not. Kuroki-Soga [13] dealt with the case where , but they missed the regularization by . The presence of does not change anything in regards to our application of Lemma 4.4 to a proof of strong convergence. *
Proof.
First we find for each fixed . Suppose that the assertion does not hold. Then, there exists some constant such that for each we can find such that
[TABLE]
where cannot stay finite as due to the presence of and we may assume as . Normalize as
[TABLE]
where and are still step functions defined on . Setting , (restriction on the grid), we see that
[TABLE]
Let be the Lipschitz interpolation of , , respectively, by means of Lemma 4.1. We have
[TABLE]
where are some constants. Hence, , are bounded sequences of ; with reasoning similar to the proof of Proposition 4.2, we find functions such that , in as (up to a subsequence), as well as , in as (up to a subsequence). On the other hand, due to the Rellich-Kondrachov theorem, taking a subsequence if necessary, we see that , strongly in as . By (4.11), we have
[TABLE]
Since , are discrete divergence-free, we have for each (restricted to the grid) and for sufficiently large ,
[TABLE]
to conclude that .
It follows from (4.10) that
[TABLE]
which implies that
[TABLE]
For each with and for all sufficiently large , we obtain with Proposition 4.3 and (4.12),
[TABLE]
Hence, with (4.12), (4.13) and (4.14), we obtain
[TABLE]
The first inequality implies . However, since , we take that approximates in the -norm as and find
[TABLE]
Since , we have , which is a contradiction. Therefore, there exists for each as claimed.
We prove that there exists independent of the choice of . Fix any . Let be the infimum of for each fixed . We will show that is bounded on . Suppose that is not bounded. Then, we find a sequence for which as . Set . For each , there exists for which we have
[TABLE]
Note that as and converges to some as (up to a subsequence); cannot stay finite as due to the presence of . Since is unbounded, we may follow the same reasoning as the first half of our proof and reach a contradiction. In fact, we obtain the limit function such that in the same way; we also obtain for all by
[TABLE]
where we use the “equi-continuity” shown in the proof of Proposition 4.3 with smooth approximation of and . ∎
Theorem 4.5**.**
The sequence mentioned in Proposition 4.2, which is weakly convergent to the weak limit , converges to strongly in .
Proof.
Re-write , as , . Suppose that does not converge to strongly in as . Then, is not a Cauchy sequence in , i.e., there exists such that for each there exist for which holds. It follows from Lemma 4.4 that
[TABLE]
where is arbitrarily chosen, is a constant and
[TABLE]
Due to (3.23) and (3.24), for any small we may chose and for which holds for all . If we prove as for each , we reach a contradiction and the proof is done.
The next step starts with a discrete version of the following obvious equality for two functions:
[TABLE]
Fix arbitrarily. Let be such that . For a fixed , let be such that . Note that for all sufficiently large . We will later appropriately choose close enough to . Define
[TABLE]
which leads to
[TABLE]
We introduce , , and in the same way with the same and , to have . Observe that
[TABLE]
We check that can be arbitrarily small as within admissible function (noting again that near and ), where we insert the discrete Navier-Stokes equations into the discrete time-derivative. Hereafter, are some constants independent of , , and admissible functions . With the discrete Navier-Stokes equations (3.8), we have
[TABLE]
We estimate the terms -. Since
[TABLE]
(3.1), (3.2) and (3.23) implies that
[TABLE]
Observe that
[TABLE]
By (2.3), (3.23) and (3.24), we obtain
[TABLE]
A similar reasoning yields
[TABLE]
By (3.2), we obtain
[TABLE]
Therefore, we see that for any (small) there exists and such that for all and all admissible , which holds for as well. On the other hand, since and weakly converge to as due to Proposition 4.2, we have
[TABLE]
where it is easy to check that the convergence is uniform within all admissible functions . Thus, we conclude that as for each and we reach a contradiction. ∎
4.3 Strong convergence of
Let be the one mentioned in Proposition 4.2 and Theorem 4.5. We extend to be [math] outside , where the extended belongs to and satisfies .
We first show that the step function generated by also strongly converges to in . For this purpose, we prove that is such that
[TABLE]
If not, we find a constant , sequences as and for each such that . Then, we see that some yields
[TABLE]
Hence, there exists such that
[TABLE]
This is a contradiction, since is bounded independently from .
Recall that is extended to be [math] outside for ; we consider the step function generated by the extended . It follows from (4.15) that for each fixed we have for all sufficiently small . Observe that
[TABLE]
Let achieve the supremum
[TABLE]
Define the step function , , where . Then, we have
[TABLE]
Fix an arbitrarily small . We have such that supp and , where is extended to be [math] outside . Since is uniformly continuous, we may choose the above so that
[TABLE]
Observe that
[TABLE]
Therefore, we have
[TABLE]
Since is arbitrary, we conclude that
[TABLE]
Furthermore, for all sufficiently small such that , where is the constant to compare and , we see that
[TABLE]
Theorem 4.6**.**
The sequence mentioned in Proposition 4.2 and Proposition 4.3, which is weakly convergent to the weak limit , converges to strongly in . Furthermore, satisfies
[TABLE]
In particular, it holds that a.e. on .
Proof.
We convert (3.6) into a weak form. First, we argue within the class of test functions with supp. Fix such an arbitrary test function . Shifting to , we have for all sufficiently small ,
[TABLE]
where we also note that near and is bounded. Similarly, we have
[TABLE]
Therefore, the weak form of (3.6) is
[TABLE]
It follows from the weak convergence of and strong convergence of in (4.19) together with (4.16) that
[TABLE]
where we note that
[TABLE]
We show that a.e. on . Take any test function such that supp and supp. Since on , (4.20) yields
[TABLE]
which implies that
[TABLE]
Hence, including such that , we have
[TABLE]
which implies that a.e. on , where has been extended to be outside .
Now, we extend the class of test functions as mentioned in (4.18). For any such test function , consider a smooth cut-off of with respect to the -variable such that supp and on . Since and a.e. , it holds that
[TABLE]
Therefore, we see that
[TABLE]
In order to prove that the weak convergence is in fact strong convergence, we use the fact that an -function satisfying (4.18) conserves its -norm, i.e.,
[TABLE]
This is shown in [4] for problems on the whole space; our current bounded domain case can be reduced to the whole space case by [math]-extension of and (see Introduction of [20]); Tenan [23] directly proved counterparts of [4] for problems on a bounded domain. The general property of weak convergence provides
[TABLE]
On the other hand, for all sufficiently small such that (4.17) holds, (3.2) with leads to
[TABLE]
(4.22) and (4.23) conclude that converges to strongly in . ∎
Corollary 4.7**.**
It holds that , in as for any .
Proof.
Let be arbitrary. It follows from Theorem 4.6 that there exists a subsequence such that a.e. as . Since is continuous, we have a.e. as . Since , Lebesgue’s dominated convergence theorem shows that as . If does not converge to in as , we have a constant and a subsequence such that for all ; however, still converges to strongly in as and we have a subsequence such that a.e. as ; this causes a contradiction. follows from the above argument with . ∎
4.4 Convergence to a weak solution
We prove the following theorem:
Theorem 4.8**.**
The pair of the limits of and is a weak solution of (1.8).
Proof.
It follows from (4.18) and (4.21) that satisfies (1).
Next, we show that and satisfy (1). Note that belongs to , because has -independent bound of due to (3.23). Take an arbitrary test function and consider sufficiently small . We have
[TABLE]
where we note that near . Similarly, we have
[TABLE]
[TABLE]
where are mentioned in Proposition 4.2. Hence, the weak form of (3.8) is
[TABLE]
We evaluate -. Hereafter, are some constants independent of . Observe that
[TABLE]
Let be an approximating sequence of in . We have
[TABLE]
where are independent from . For any , fix so that . Since is uniformly continuous on , we have
[TABLE]
Since is arbitrary, we conclude that
[TABLE]
Theorem 4.2, Theorem 4.5, Theorem 4.6 and Corollary 4.7 yield
[TABLE]
where we note that in as . Observe that
[TABLE]
Hence, we obtain
[TABLE]
It follows from (3.2) that as . (4.16) implies that as . ∎
Acknowledgement. This paper was written during author’s one-year research stay in Fachbereich Mathematik, Technische Universität Darmstadt, Germany, with the grant Fukuzawa Fund (Keio Gijuku Fukuzawa Memorial Fund for the Advancement of Education and Research). The author expresses special thanks to Professor Dieter Bothe for his kind hosting in TU-Darmstadt. The author is supported by JSPS Grant-in-aid for Young Scientists #18K13443 and JSPS Grants-in-Aid for Scientific Research (C) #22K03391.
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