Abstract
This paper presents a robust fitted mesh finite difference method for solving a dynamical system of two parameter convection–reaction–diffusion delay differential equations defined on the interval . The method incorporates a piecewise uniform Shishkin mesh to accurately resolve the solution behavior caused by small perturbation parameters and delay terms. The proposed numerical scheme is proven to be parameter-robust and achieves almost first-order convergence. Numerical illustrations are provided to showcase the method’s effectiveness, highlighting its capability to address boundary and interior layers with improved accuracy. The results, supported by symmetrical considerations in the figures, enhance the precision and serve as validation for the theoretical results.
Keywords:
singularly perturbed delay differential equations; numerical methods; convection–diffusion; Shishkin meshes; boundary layer; uniform convergence MSC:
65L11; 65L12; 65L20; 65L50; 65L70
1. Introduction
Singularly perturbed differential equations (SPDEs) emerge in numerous scientific and engineering fields, such as fluid dynamics, chemical reactor theory, population dynamics, particle fluid motion [], and control theory []. A notable subset of these equations is the singularly perturbed delay differential equations (SPDDEs); these equations are characterized by the presence of two distinct small perturbation parameters, which introduce additional complexities due to the occurrence of boundary and interior layers. These layers arise because of the small perturbation parameters and delay terms, making the numerical approximation of SPDDEs particularly difficult. To tackle these challenges, numerous specialized numerical techniques, including fitted mesh methods [] and fitted operator methods [], are developed and well established. This approach offers robust and precise solutions to singularly perturbed differential equations (SPDEs). For instance, Cen [] analyzed a class of first-order SPDDEs utilizing a hybrid difference scheme combined with a piecewise uniform Shishkin mesh, demonstrating that the approach achieves near second-order convergence. Gracia, O’Riordan, and Pickett [] stated that a singularly perturbed ordinary differential equation is influenced by two small parameters that impact both the convection and diffusion terms. They proposed a second-order monotone numerical method to solve the problem. In [], parabolic singularly perturbed parabolic differential equations involving two parameters on a rectangular domain were examined.
SPDDEs are typically defined a system of boundary value problems influenced by two small parameters, and . The interaction between these parameters produces intricate layers, determined by the ratio . This work has focused on developing parameter-robust methods for solving these equations, especially as both and approach zero simultaneously. The most important papers among all are [,,]. This paper focuses on the numerical solution of a boundary value problem for SPDDEs with two small perturbation parameters. The interaction between these parameters introduces complex, symmetry-influenced layer patterns in the solution, further compounded by the delay term. Our goal is to construct a parameter-robust numerical method that ensures the accurate solution of boundary and interior layers, regardless of the perturbation parameters. In doing so, we aim to establish the minimum principle and stability result of the solution and derive bounds for the solution’s derivatives to support the convergence analysis of the proposed fitted mesh finite difference method, which will achieve nearly first-order convergence, regardless of the two perturbation parameters, and offer a robust layer-solving solution. Several studies have addressed singular perturbation problems, focusing on their asymptotic properties, parameter-uniform methods, and delay differential equations to ensure robust and accurate solutions across varying parameters [,,].
The novelty of this paper lies in its approach to solving a system of two-parameter singularly perturbed delay differential equations (SPDDEs) of the convection–diffusion type. Unlike previous works, such as [], which focuses on single delay differential equations, and [], which addresses a system of convection–reaction–diffusion equations without delay terms, this paper considers interacting variables influenced by both delay and two distinct small perturbation parameters. This dual influence introduces significant complexities, particularly in the formation of boundary and interior layers. To tackle these challenges, a more robust numerical scheme integrating advanced mesh techniques, such as the use of a piecewise uniform Shishkin mesh, is proposed. Furthermore, this method employs more robust numerical schemes and advanced mesh techniques, potentially achieving almost first-order convergence, independent of the two perturbation parameters.
2. Formulation of the Problem
3. Analytical Results
This section presents a minimum principle and a stability result, and it provides estimates for the derivatives of the solution to the problem defined by Equation (1).
Lemma 1.
Let be such that , , on and on , , then on .
Proof.
Assume that and be such that . Suppose . Then, cannot be at the boundaries 0 or 2. At , the first derivative of , denoted as and the second derivative . Claim (i): .
If , then
which contradicts the assumption that on . Thus, . Claim (ii): . If , then
which contradicts the assumption that on . Hence, . When , the differentiability of at is investigated. If does not exist, then , which contradicts the condition . If is differentiable at , then . Since all entries of , , and are continuous on , there is an interval where . If for any , then , which leads to a contradiction. Therefore, it is assumed that on the interval . This indicates that is strictly decreasing over . Given that and is continuous on , it follows that on . As a result, the continuous function cannot attain a minimum at , which contradicts the assumption that . Thus, on . The proof of the lemma is complete. □
Lemma 2.
(Stability Result) Let . For ,
Proof.
Define
Consider the functions , where . Clearly, ; at both 0 and 2, is non-negative, i.e., and . For ,
and for ,
Also, is equal to , both of which are zero, i.e., and , then By applying Lemma 1, it is obtained that for . The proof of the lemma is complete. □
Theorem 1.
Let be the solution of (1); then, its derivatives satisfy the following bounds on Ω,
where the constant C is independent of and μ, i, k = 1, 2.
Proof.
The proof follows the methodology outlined in Lemma 2.2 of []. For any , a neighborhood can be constructed in such a way that and . According to the mean value theorem, there is a satisfying
Now,
Thus,
The bounds for are obtained from Equation (1) and the bounds from Equation (7) for . Similarly, the bounds of and can be established for higher-order derivatives through analogous corresponding manipulations. The proof of the theorem is complete. □
4. Shishkin Decomposition of the Solution
For each of the cases and , is expressed by
where
Case (i):
In this case,
Case (ii):
In this case,
To ensure the jump conditions at in Equations (13) and (22) are satisfied, the constants and must be selected appropriately. Additionally, the constants and should be determined independently for the cases and , ensuring they meet the bounds required for the singular component. Given that and are bounded by constants that do not depend on and , even though , , , and are functions of and , the magnitudes , , , and are constants independent of and .
5. Bounds on the Regular Component and Its Derivatives
Case (i):
Establishing the bounds of the regular components and , they are broken down as in []
where , and their respective equations are on the intervals and , where and , are defined by
where Equations (33)–(37) give
Now, from (39)–(42) and using Lemma 2, . Using the estimates . From the defining equation of in (39),
Decomposing as where
using the above, are found and then, from (46), , , . By differentiating the defining equation of once and using the bounds of and , the following bound is obtained. Now, by choosing
from the above, it is derived that
Similarly,
Case (ii):
Establishing the bounds of the regular components and , they are broken down as
where , .
To estimate the smooth components and for , the decomposition of and is analyzed on two levels. Furthermore, the maximum principle for a linear first-order operator in the context of a terminal value problem is established. Define the operators
Consider the following decompositions:
where , are defined as follows:
where , and . Here, and are given functions, and the functions and are chosen to satisfy the boundary and continuity conditions.
Lemma 3.
Let with and . If on and on , then on .
Proof.
Let be a point, where . Assume for contradiction that ; this implies that and . If . Then, this can analyzed as
which contradicts the assumption that on . Furthermore, if
which also leads to a contradiction. Thus, on .
The decomposition of and is given by
where
Since , , , and are sufficiently smooth, it follows that
Using Lemma 3, it can be proved that , , , . Also, from (73),
Hence, choosing
yields for and for . Similarly, finding , and and using Lemma 3, , and . Utilizing the bounds from Theorem 1, the resulting estimates are as follows:
Also, from the equation of in (65),
and these bounds are obtained
Differentiating the equation of and using the bounds of and its derivatives,
similarly,
Hence,
and by utilizing all the aforementioned bounds, the bounds of the regular component are obtained by
Similarly, it can be determined that
The proof of the lemma is complete. □
6. Layer Functions
The functions for the layers are denoted by and and are specified over the interval ,
The layer functions are specified over ,
where ; ; , for . Following the Lemma 5 presented in [], the points , which satisfy the conditions for the case , can be proved.
Similarly, for the case , it can be shown that there are points in such that
7. Bounds on the Singular Component and Its Derivatives
Theorem 2.
Let satisfy problems (16), (19) and (25), (28) for the cases and , respectively. Consequently, the components of and satisfy the following bounds on .
For the case ,
For the case ,
Moreover, the components satisfy the following bounds of . For the case ,
For the case ,
Components of and on , for the case ,
For the case ,
Moreover, the components satisfy the following bounds of . For the case ,
For the case ,
Proof.
The bounds on and its derivatives are established for the case . In this scenario, is decomposed over the interval .
where , , and their equations are given as follows:
It can be easily derived from Equations (85)–(87) that,
Also, from the equation of in (88) using Theorem 1 and the fact that , the following can be derived:
Consider the equation of in (88), which can be written as,
The decomposition of is as follows:
where are characterized by,
From the above equations,
By applying Theorem 3 of [], the following bounds are established by
Using , and , the following bounds of are obtained by
Now, using the bounds of , and and
using the above bounds, the following bounds of and its derivatives are found for
For the case , we define the barrier functions , where for . It is evident that and . Additionally, for all x in the interval . Therefore, it can demonstrate that and .
Considering the equation of from (25),
This can also be written as,
where
Now, taking ,
where is the indefinite integral of . Using the bounds on , it is established that . Using the inequality and applying integration by parts, it is derived from the above that
Using a similar argument, it can be
Differentiating the equation and using a similar procedure as above, it can be shown that
Similarly,
The bounds on can be obtained from the equation of in (25) and the bounds on , , and . The bound on is obtained by differentiating the equation of in (25) twice and using a similar argument as above. Now, by differentiating the defining equation of in (25) once and using the bounds on , and , the following can be derived below
It has been established that
Consequently,
where
By introducing the barrier function
it can be demonstrated that on and which implies
By introducing another barrier function
it is derived that
By differentiating the equations of and once and applying the bounds of , , , and , it is found that
Similarly, analogous results can be derived for on .
Next, the bounds on for the case are derived. The bounds on and can be derived by defining the barrier functions
To bound and , the argument proceeds as follows, and from the equation of in Equation (16) and Theorem 1, it is obtained that . From the equation of in (16) and Theorem 1, . To improve the above bound on , proceed with the following and differentiate in (16) once, obtaining
To establish the necessary bounds, define the barrier functions as follows:
and apply the minimum principle for the operator . The bound on is obtained from the equation of in (16). To bound and , the defining equation of in (16) is differentiated twice and thrice, respectively, and an argument analogous to the one used to bound leads to the required bounds. The bound on is obtained by differentiating the defining equation of in (16) once and using the bounds of , , , and ; it can be seen that
Similarly, using an analogous way, it can be derived for on [1,2].
For the case , the bounds on are obtained by the above analogous arguments to those applied in bounding . The proof of the theorem is complete. □
8. Sharper Bounds for and
To achieve sharper bounds on the derivatives of the singular components , and , decompose these components further for [0,1] and [1,2]. This refinement will help to demonstrate the nearly first-order convergence of the proposed method. Now, focusing on the case . For and , decompose it as follows: on [0,1] and on [1,2]. Decompose of
where
Decompose of
where
Decompose of
where
Decompose of
where
Lemma 4.
Given the decompositions of , and , the following bounds hold on [0,1]:
Similarly, the decompositions of and , the following bounds hold on [1,2]:
Proof.
For ,
On
On
.
For , On
On .
For and , similar bounds are obtained. For [1,2], is considered and on
On
.
For , on
On
.
For and , similar bounds are obtained. Similarly, find the sharper bounds for the case . In this scenario, the decomposition of and remains as before. The proof of the lemma is complete. □
Lemma 5.
Given the decompositions of , and , the following bounds hold on [0,1]:
and given the decompositions of and , the following bounds hold for [1,2]:
Proof.
The proof follows the same logic as Lemma 4. □
Analogously, the decompositions can be made for and in both cases. Corresponding bounds for these components can be similarly demonstrated in a similar manner.
9. Numerical Method
This section presents the proposed numerical method for solving (1) and utilizing a Shishkin mesh for the discretization.
For the cases and , appropriate Shishkin meshes are developed over interval .
Case (i):
In this case, the Shishkin mesh for over the interval is determined by the transition parameters and . The interval is partitioned into the subintervals , , , , ,,, , , and , where and are defined as,
Each of the intervals , , , , , , , and are divided into subintervals, while the intervals and are divided into subintervals. When and , the mesh is uniform. Let , , and denote the step sizes on the intervals , , and , respectively. Thus, The step sizes in the intervals and are and , respectively. Based on the selection for and , there are four possible meshes in this case.
Case (ii):
In this case, the Shishkin mesh for on is defined by the transition parameters , , and . The interval is divided into the subintervals , , , , ,, , and , where , , and are defined as
Each of the intervals , , , and is divided into subintervals, the intervals and are divided into subintervals, and the intervals and are divided into subintervals. Let the step length for each of the intervals be , , , and let be denoted by , , , and , respectively. Thus, Although there are eight possible meshes resulting from the various options for the transition parameters, , should take the value . Otherwise, the case of inequality would be true, leading to a contradiction. Therefore, there are only six possible meshes in this case.
10. The Discrete Problem
The discrete problem is defined as follows:
with boundary conditions specified as follows:
Let
The discrete derivatives are defined as
with
11. Numerical Results
This section establishes a discrete minimum principle, a discrete stability result, and the first-order convergence of the proposed numerical method.
Lemma 6.
(Discrete Minimum Principle) Assume that the mesh function satisfies and . Then, if for , for , and it implies that for all .
Proof.
Let and be such that and suppose . Then, , , and .Therefore, Conside the two cases, for , if , then
which is a contradiction, which gives . For ,if , then
which is a contradiction, which gives . The only remaining possibility is that . Thus, by hypothesis, it follows that
This implies
and since , it follows that
Consequently, it follows that
Now, consider the operator acting on the solution at
leading to a contradiction, implying that for all . □
Lemma 7.
(Discrete Stability Result) If is any mesh function, then
Error Estimate
Analogous to the continuous case, the discrete solution can be decomposed into and as defined below.
It is clear that
Proof.
Hence,
Determining the local truncation error
for . It is established that . In this case , from (53) and (54),
Using Lemma 7, consider the mesh function,
Provided that the value of C is sufficiently large, it follows that
Similarly,
For the case
Similarly,
It can be stated that for both cases,
Thus,
The proof of the lemma is complete. □
The bounds on the error in the singular components and are estimated for the case , utilizing the mesh functions defined on ,
with for p = 1,2.
Lemma 9.
For the case , the layer components and satisfy the following bounds on :
Proof.
This result can be demonstrated by defining the mesh functions ; ; i = 1, 2; and p = 1, 2 and noticing that and . Furthermore, and . Therefore, the discrete minimum principle provides the desired outcome. The proof of the lemma is complete. □
Proof.
The local truncation error is given by
where . When and , the mesh is uniform; then, the value of . In this instance, , and .
Develop the mesh functions that were specified in by
where is a constant and it satisfies ,
The mesh functions described above are inspired by those constructed in []. Now, that , , , and . Then, define . It is easy to observe that and . Hence, by applying minimum principle,
Similarly,
Now, when , for the mesh elements , for
Similarly,
For
Similarly,
When , there are two distinct cases that are considered: and . In the case , for , . Hence,
For
For this case, for ; using the decomposition of and , the following results are derived based on (95)–(98). Let ; then,
For
For , ,
For ,
Let us define the mesh functions on the domain for the value of j such that , and for as follows:
and for and as
By defining the barrier functions for and utilizing the minimum principle, it can be established that for all . Similarly, by defining the barrier functions for and utilizing the minimum principle, it can be established that for all . Consequently, it follows that
Now, consider the case , , and . In this scenario, . For , it follows that . Hence,
For , it follows that . Hence,
For , by utilizing the decomposition in the previous case, the following is derived
For ,
Similarly, for , it follows that . Hence,
For , it follows that . Hence,
Finally, by utilizing the minimum principle along with the specified barrier functions, the required bounds can be obtained. Let , where is defined for and for as follows:
and for and as
and for and for as
Thus, for each of the cases, the barrier function is constructed, and, using maximum principle, it has been derived that
Therefore,
The proof of the lemma is complete. □
For the case , the error in the component is bounded as follows:
Proof.
The local truncation error is given by
For and , with a uniform mesh size , it follows that and ,
Consider the intervals separately for the case when and , for
For , using the decomposition of and , it follows that
For
For , it follows that ; then,
For
To estimate this bound, the following mesh functions are defined on
with , for , for . When and , it follows that ; hence, . For , it follows that
Similarly,
For , it follows that
Similarly,
When or , . Therefore,
For
When or , , and the required bounds are derived as
When and and when or ,
For or , analogous arguments to those applied in the corresponding intervals of earlier cases yield the required bounds, ,
For or ,
When or , . Hence,
For or ,
Therefore,
The proof of the lemma is complete. □
For the case , the error in the component is bounded as follows:
Lemma 12.
When is decomposed as in (84), the following bounds hold .
Proof.
Decomposition of (84),
Let , where C is chosen to be sufficiently large and it is evident that . Additionally, it is known that as defined in Lemma 3. By utilizing the minimum principle, it follows that , leading to the inequality
Using this result and Equation (85), the bound is derived as follows:
By differentiating Equation (85) and applying the previous bounds, it is obtained that
Thus,
Next, considering and using the established bounds on and their derivatives, it is concluded that
Similarly, it is found that
By combining all these results, the bound is obtained as follows: for [0,1]. Analogously, it is easy to find for [1,2]. The proof of the lemma is complete. □
Lemma 13.
The singular component and for the case satisfies the following bounds:
Proof.
Utilizing the previous lemma, deriving the above bound is not hard. To establish the bounds on the error , the mesh function is defined over
Now, consider and . Also, since , . Hence, . Also, for an appropriate choice of C, it follows that . Further, and . Hence, by the minimum principle, and , for . Hence, similarly, it can be stated for ,
The proof of the lemma is complete. □
Lemma 14.
At each point , , for the case .
Proof.
The local truncation error is given by
where . Consider the case . Hence,
for
Examine the mesh region ; it is known that , then,
For
When . Hence,
Thus,
The proof of the lemma is complete. □
From the previous Lemmas 10–14, for , analogously is obtained.
Theorem 3.
Proof.
The proof follows Lemmas 8, 10, 11, and 14. □
12. Numerical Illustration
Example
The numerical approximated the solution to the following system on the interval , applying the proposed method to both cases where and
with boundary conditions specified as and .
To evaluate the order of convergence, maximum pointwise errors, and error constants, a modified two-mesh algorithm was utilized. The findings are summarized in Table 1 and Table 2. Notably, as decreases, the error stabilizes for each N, while the maximum error reduces with increasing N. Furthermore, the order of convergence rises as N increases, confirming the theoretical results.
Table 1.
Values of , and when for .
Table 2.
Values of , and when for .
Figure 1 and Figure 2 illustrate the graphs of the solutions obtained and demonstrate how symmetry in the layers contributes to the accuracy and validation of the theoretical results. In Figure 1, where the ratio , boundary layers for and are observed near , , and , which is consistent with expectations. In contrast, Figure 2 shows that when , the initial layers for and are present near , while boundary layers appear for both and near and a delay appears near .
Figure 1.
Graphical representation of numerical solutions for the case .
Figure 2.
Graphical representation of Numerical solutions for the case: .
13. Conclusions
In this paper, a robust fitted mesh finite difference method is introduced for solving a system of two-parameter singularly perturbed delay differential equation of the convection–reaction–diffusion type. By employing a piecewise uniform Shishkin mesh, our robust fitted mesh method effectively addresses the complexities arising from two distinct small perturbation parameters, delay terms, and resolved boundary and interior layers in SPDDEs. The theoretical analysis confirms that the proposed scheme achieves almost first-order convergence in the maximum norm, independent of these two distinct perturbation parameters. Numerical illustrations validate the method’s effectiveness, showcasing its ability to resolve intricate boundary and interior layers. This work highlights the importance in numerical techniques for SPDDEs and lays the groundwork for further advancements. Future research could focus on extending this methodology to multidimensional and time-dependent problems, exploring adaptive mesh strategies and applying the approach to real-world applications in engineering and science.
Author Contributions
Conceptualization, J.P.M.; methodology, J.A. and J.P.M.; software, J.P.M. and J.A.; validation, J.P.M., G.E.C. and S.L.P.; formal analysis, J.A. and J.P.M.; investigation, J.A., J.P.M. and G.E.C.; resources, J.P.M. and J.A.; data curation, J.A. and J.P.M.; writing—original draft preparation, J.A. and J.P.M.; writing—review and editing, J.A., J.P.M., G.E.C. and S.L.P.; visualization, J.A.; supervision, G.E.C. and J.P.M.; project administration, J.P.M. and G.E.C.; funding acquisition, G.E.C. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Data Availability Statement
Data is contained within the article.
Conflicts of Interest
The authors declare no conflicts of interest.
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