A new conservative finite difference scheme is presented for an initial-boundary value problem of the general Rosenau-RLW equation. Existence of its difference solutions are proved by Brouwer fixed point theorem. It is proved by the discrete energy method that the scheme is uniquely solvable, unconditionally stable, and second-order convergent. Numerical examples show the efficiency of the scheme.
1. Introduction
In this paper, we consider the following initial-boundary value problem of the general Rosenau-RLW equation:
(11)with an initial condition
(12)and boundary conditions
(13)where
is a integer and
is a known smooth function. When
, (1.1) is called as usual Rosenau-RLW equation. When
, (1.1) is called as modified Rosenau-RLW (MRosenau-RLW) equation. The initial boundary
value problem (1.1)–(1.3) possesses the following conservative quantities:
(14)
(15)It is known the conservative scheme is better than the nonconservative ones. Zhang
et al. [1] point out that the nonconservative scheme may easily show nonlinear blow up. In
[2] Li and Vu-Quoc said "
in some areas, the ability to preserve some invariant properties of the original
differential equation is a criterion to judge the success of a numerical simulation".
In [3–11], some conservative finite difference schemes were used for a system of the generalized
nonlinear Schrödinger equations, Regularized long wave (RLW) equations, Sine-Gordon
equation, Klein-Gordon equation, Zakharov equations, Rosenau equation, respectively.
Numerical results of all the schemes are very good. Hence, we propose a new conservative
difference scheme for the general Rosenau-RLW equation, which simulates conservative
laws (1.4) and (1.5) at the same time. The outline of the paper is as follows. In
Section 2, a nonlinear difference scheme is proposed and corresponding convergence
and stability of the scheme are proved. In Section 3, some numerical experiments are
shown.
2. A Nonlinear-Implicit Conservative Scheme
In this section, we propose a nonlinear-implicit conservative scheme for the initial-boundary value problem (1.1)–(1.3) and give its numerical analysis.
2.1. The Nonlinear-Implicit Scheme and Its Conservative Law
For convenience, we introduce the following notations
(21)where
and
denote the spatial and temporal mesh sizes,
,
, respectively,
(22)and in the paper,
denotes a general positive constant, which may have different values in different
occurrences.
Since
, then the finite difference scheme for the problem (1.1)–(1.3) is written as follows:
(23)
(24)
(25)Lemma 2.1 (see [12]).
For any two mesh functions,
, one has
(26)Furthermore, if
, then
(27)Theorem 2.2.
Suppose that
, then scheme (2.3)–(2.5) is conservative in the senses:
(28)
(29)Proof.
Multiplying (2.3) with
, according to boundary condition (2.5), and then summing up for
from 1 to
, we have
(210)Let
(211)Then (2.8) is gotten from (2.10).
Computing the inner product of (2.3) with
, according to boundary condition (2.5) and Lemma 2.1, we obtain
(212)where
(213)According to
(214)we have
. It follows from (2.12) that
(215)Let
(216)Then (2.9) is gotten from (2.15). This completes the proof of Theorem 2.2.
2.2. Existence and Prior Estimates of Difference Solution
To show the existence of the approximations
for scheme (2.3)–(2.5), we introduce the following Brouwer fixed point theorem [13].
Lemma 2.3.
Let
be a finite-dimensional inner product space,
be the associated norm, and
be continuous. Assume, moreover, that there exist
, for all
,
,
. Then, there exists a
such that
and
.
Let
,
, then have the following.
Theorem 2.4.
There exists
which satisfies scheme (2.3)–(2.5).
Proof.
It follows from the original problem (1.1)–(1.3) that
satisfies scheme (2.3)–(2.5). Assume there exists
which satisfy scheme (2.3)–(2.5), as
, now we try to prove that
, satisfy scheme (2.3)–(2.5).
We define
on
as follows:
(217)where
. Computing the inner product of (2.17) with
and considering
and
, we obtain
(218)Hence, for all
,
there exists
. It follows from Lemma 2.3 that exists
which satisfies
. Let
, then it can be proved that
is the solution of scheme (2.3)–(2.5). This completes the proof of Theorem 2.4.
Next we will give some priori estimates of difference solutions. First the following two lemmas [14] are introduced:
Lemma 2.5 (discrete Sobolev's estimate).
For any discrete function
on the finite interval
, there is the inequality
(219)where
are two constants independent of
and step length
.
Lemma 2.6 (discrete Gronwall's inequality).
Suppose that the discrete function
satisfies the inequality
(220)where
and
are nonnegative constants. Then
(221)where
is sufficiently small, such that
.
Theorem 2.7.
Suppose that
, then the following inequalities
(222)hold.
Proof.
It is follows from (2.9) that
(223)According to Lemma 2.5, we obtain
(224)This completes the proof of Theorem 2.7.
Remark 2.8.
Theorem 2.7 implies that scheme (2.3)–(2.5) is unconditionally stable.
2.3. Convergence and Uniqueness of Difference Solution
First, we consider the convergence of scheme (2.3)–(2.5). We define the truncation error as follows:
(225)then from Taylor's expansion, we obtain the following.
Theorem 2.9.
Suppose that
and
, then the truncation errors of scheme (2.3)–(2.5) satisfy
(226)as
, 
Theorem 2.10.
Suppose that the conditions of Theorem 2.9 are satisfied, then the solution of scheme
(2.3)–(2.5) converges to the solution of problem (1.1)–(1.3) with order
in the
norm.
Proof.
Subtracting (2.3) from (2.25) letting
(227)we obtain
(228)Computing the inner product of (2.28) with
, we obtain
(229)From the conservative property (1.5), it can be proved by Lemma 2.5 that
. Then by Theorem 2.7 we can estimate (2.29) as follows:
(230)According to the following inequality [11]
(231)Substituting (2.30)–(2.31) into (2.29), we obtain
(232)Let
(233)then (2.32) can be rewritten as
(234)Choosing suitable
which is small enough, we obtain by Lemma 2.6 that
(235)From the discrete initial conditions, we know that
is of second-order accuracy, then
(236)Then we have
(237)It follows from Lemma 2.5, we have
. This completes the proof of Theorem 2.10.
Theorem 2.11.
Scheme (2.3)–(2.5) is uniquely solvable.
Proof.
Assume that
and
both satisfy scheme (2.3)–(2.5), let
, we obtain
(238)Similarly to the proof of Theorem 2.10, we have
(239)This completes the proof of Theorem 2.11.
Remark 2.12.
All results above in this paper are correct for initial-boundary value problem of the general Rosenau-RLW equation with finite or infinite boundary.
3. Numerical Experiments
In order to test the correction of the numerical analysis in this paper, we consider the following initial-boundary value problems of the general Rosenau-RLW equation:
(31)with an initial condition
(32)and boundary conditions
(33)where
. Then the exact solution of the initial value problem (3.1)-(3.2) is
(34)where
is wave velocity.
It follows from (3.4) that the initial-boundary value problem (3.1)–(3.3) is consistent
to the boundary value problem (3.3) for
. In the following examples, we always choose
,
.
Tables 1, 2, and 3 give the errors in the sense of
-norm and
-norm of the numerical solutions under various steps of
and
at
for
and
. The three tables verify the second-order convergence and good stability of the numerical
solutions. Tables 4, 5, and 6 shows the conservative law of discrete mass
and discrete energy
computed by scheme (2.3)–(2.5) for
and
.
Table 1. The errors of numerical solutions at
with
for
.
Table 2. The errors of numerical solutions at
with
for
.
Table 3. The errors of numerical solutions at
with
for
.
Table 4. Discrete mass
and discrete energy
with
at various
for
.
Table 5. Discrete mass
and discrete energy
with
at various
for
.
Table 6. Discrete mass
and discrete energy
with
at various
for
.
Figures 1, 2, and 3 plot the exact solutions at
and the numerical solutions computed by scheme (2.3)–(2.5) with
at
, which also show the accuracy of scheme (2.3)–(2.5).
Acknowledgments
The authors would like to express their sincere thanks to the referees for their valuable suggestions and comments. This paper is supported by the National Natural Science Foundation of China (nos. 10871117 and 10571110).
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Figure 1.
at
and numerical solutions computed by scheme (2.3)–(2.5) at
for
.
Figure 2.
at
and numerical solutions computed by scheme (2.3)–(2.5) at
for
.
Figure 3.
at
and numerical solutions computed by scheme (2.3)–(2.5) at
for
.
