Abstract
We prove that the steady states of a class of multidimensional reaction–diffusion systems are asymptotically stable at the intersection of unweighted space and exponentially weighted Sobolev spaces, paying particular attention to a special case, namely, systems of equations that arise in combustion theory. The steady-state solutions considered here are the end states of the planar fronts associated with these systems. The present work can be seen as a complement to the previous results on the stability of multidimensional planar fronts.
1. Introduction
In this paper, we study the stability of the steady states of a class of reaction–diffusion systems associated with combustion problems in multidimensional cases. We study the following system of general reaction diffusion equations for :
where is the vector of the temperature and the substances taking part in the reactions, the diagonal matrix is the transport coefficient matrix (the coefficients of thermal diffusivity and diffusion coefficients), and the non-linear term in the system is used to describe the reaction rate of each substance. We later provide several hypotheses on the nonlinear terms of this general system that allow us to apply the methods in this paper. A typical example is the following system:
where the reaction rate has an Arrhenius temperature dependence
While we assume in this paper, note that d usually has a definite physical meaning only when or 3 is adopted. Here, and denote the dimensionless temperature and concentration of the initial substance, respectively, is the ratio of the coefficient of diffusion to the coefficient of heat conduction, and is the stoichiometric coefficient, which satisfies and . Chemical reaction waves turn one equilibrium state into another; here, we consider combustion waves that involve a strong temperature dependence in the reaction rate. Following the conventions of combustion theory, we assume that the chemical reaction rate is so small at low temperatures compared to the maximum temperature of the combustion wave that their rates can be assumed, to a fairly good approximation, to be equal to zero ([1]), which in the mathematical formulation means setting a cut-off, as in (3).
The class of systems (1) permits various types of traveling wave solutions. Traveling waves are waves that maintain a certain shape while propagating at a fixed speed in a medium; they are widely present in a variety of natural phenomena modeled by nonlinear evolutionary equations that often describe chemical or physical processes shifting from one equilibrium state to another. We consider a traveling wave solution moving in the direction of a given vector with a constant speed , and without loss of generality, we assume that . In (1), we employ a t-dependent change of variables and re-denote again. Then, system (1) in this moving coordinate system becomes
In particular, we focus on the steady states of the wave fronts. By wave fronts, we mean solutions of system (1) having limits ,
where meaning that satisfies the ordinary differential equation
Under circumstances of physical interest, these solutions approach both end states and at an exponential rate. The end states are usually not independent as such; a detailed discussion can be found in [2] (Chapter 8). We use Model (2) in Remark 1 as an example to illustrate how the states are chosen.
There have been a large number of papers devoted to the study of the existence and stability of combustion waves. In particular, when , we consider
with the end conditions , , , and . Setting and considering as an independent variable, we obtain
with conditions , , and . With the aid of estimates of from the above equations, the existence of solutions is established (cf. [3]). The wave speed c, as an important characteristic of combustion waves, is obtained mainly by approximate analysis and asymptotic methods, and in many cases analytical investigations are complemented by numerical studies.
In this paper, we focus on the stability of the steady states of this type of systems. In the physical and mathematical senses, instability can be understood as sensitivity to perturbations, i.e., the possibility that the propagation of a traveling wave is distorted or altered from the system state due to a perturbation, which eventually leads to abnormal appearance or abnormal steady-state output. A more precise definition can be found in [4]. B. Sandstede and A. Scheel [5], having analysed various instability mechanisms in reaction–diffusion systems, base their classification on the type of spectrum on the imaginary axis of the linear operator from linearization of the system. One particular case involves the essential instability [5] that arises when the essential spectrum (defined as consisting of all points on the spectrum that are not isolated eigenvalues of finite multiplicity (see [6], Chapter 5) crosses the imaginary axis. At this point, the proof of nonlinear stability is based upon the use of exponential weights for the essential spectrum (see, e.g., [7,8]) and on renormalization techniques to show that the nonlinear terms are asymptotically independent compared to linear diffusion.
The purpose of using an exponentially weighted space is that this usually allows one to shift the essential spectrum, which would otherwise cross the imaginary axis, to the left half of the complex plane, allowing the exponentially decaying properties of the associated semigroup to be used. An application of this approach to reaction diffusion equations can be found in a series of papers [9,10,11,12,13] which demonstrate the orbital stability of the traveling front by studying perturbations that are small in both unweighted and weighted Sobolev spaces. Subsequently, in [14], the authors established the existence of a stable foliation near the traveling front solution of the reaction diffusion system in one-dimensional space, i.e., the existence of a central manifold at each point on the front solution that attracts nearby solutions that are slightly perturbed to the front solution itself or to one of its translations. This result complements the orbit stability results in [11]. Then, in [15], the same authors extended the stability results for the traveling front solution of the reaction–diffusion system associated with the combustion model in [11] to a multidimensional case. However, the result in [15] was formulated under the assumption that the diffusion coefficients of the variables are identical, although this assumption often does not satisfy the characteristics of reaction–diffusion systems in reality.
2. Methods
To study the stability of , we can perturb the function by either:
- (i)
- adding a function that depends only on one space variable z, that is, considering the solution of (4) with the initial conditionwith some with some in the appropriate function space constructed later; or by
- (ii)
- adding a function that depends on all spatial variables, that is, considering the solution of (4) with the initial conditionwith some from an appropriate function space.
Note that under the first type of perturbation, the problem is indeed very similar to [11], except that the spatial variables are multidimensional. Thus, we focus here on the stability of the steady state of the front of system (4) under the second type of perturbation. The main advance of this paper compared to previous works is the extension of the result in [11] for a system of one-dimensional spatial variables to a system of multidimensional spatial variables, along with the absence of the assumption in [15] that the diffusion coefficients are the same for different system variables. Moreover, as we describe in the text, this type of equation has a special “product triangle” structure in the nonlinear reaction terms which is similar to the equations studied in the one-dimensional case from [10,11,12]; this class of nonlinear terms often appears in combustion models.
To better demonstrate how this “product triangle” structure can help to study the stability of the steady states, we begin with model case (2) for ; in the moving coordinates , this system becomes
where .
According to the discussion presented earlier, a front solution is t-independent and approaches the constant states and as . System (5) has two types of steady state solutions: one when equals a real constant and , and the other when and is equal to a real constant. In particular, we can choose , which is the equilibrium corresponding to the completely burned reactants located behind the front, and , corresponding to the unburned substances. In other words, we choose and . For a more detailed explanation of why and are chosen in this way, see [10] and Remark 1.
Here, we discuss in detail only the stability of , as the stability of can be proven in precisely the same manner. We investigate perturbations of the state that depend on all spatial variables of the system, that is, we consider the solutions of (5) with the initial conditions
where is taken from an appropriate function space. Substituting into system (5), we have
Linearizing the nonlinearity at provides
where we introduce the nonlinear term by
Therefore, we have the following semi-linear equation for the perturbations of state :
We show that the spectrum of the linear operator in (8) touches the imaginary axis in Section 3, meaning that the weight function needs to be introduced in order to further investigate the stability of the system under perturbations.
For , being the Sobolev spaces , and we often define ), which are suited for the study of nonlinear stability because they are closed under multiplication, we denote the norm in by . Furthermore, we define the weight function of class by
For a fixed weight function , we define with the norm . Note that by this definition. Here and below, we use the fact that can be written as the tensor product . For general results on tensor products and operators on tensor products, refer to [16] (Volume I, Section VIII.10). For ease of notation, we use to denote the weighted Sobolev space.
Although this weighted functional space solves the problem of the spectral instability of the linear operator, it poses a new difficulty in that the nonlinear terms cannot be controlled in the weighted space. Hence, we introduce a new space using the approach originally proposed in [8] in the context of the Hamiltonian:
We prove the following theorem at the end of Section 3. Specifically, when considered in coordinates moving with fronts, we can show that the steady state of a nonlinear model problem with the form (5) is asymptotically stable in an orbital sense in a carefully chosen exponentially weighted space, i.e., the solution near the steady state converges exponentially to the steady state solution itself in the weighted norm as long as the initial perturbation is sufficiently small in both the weighted and unweighted norm.
Finally, in Section 4, we summarize a number of key features of the system used in the model problem (2), then generalize them into hypotheses; thus, for the general system (1), we can prove the stability of the steady state of a traveling front when it satisfies these hypotheses. Moreover, these hypotheses are often very common in reaction–diffusion systems associated with combustion problems.
Remark 1.
To conclude this section, we explain why the end states and were chosen as and for the model system
where g is defined in (3).
Let be a time-independent solution of the model system such that Φ satisfies the ODE system
Such solutions represent traveling combustion fronts. Here, the left temperature is an unknown to be determined.
In the ODE system (11), we set and , and use prime to denote the derivative with respect to z to obtain the following first-order system:
This expression can be integrated once to produce a function of z that is constant along any traveling wave. We denote this constant by k, meaning that
3. Stability of the Steady States for the Model Case
In this section, we study the stability of the state of systems of the model problem (2). This section is organized as follows. We study the spectrum of the operator generated by linearizing (5) with respect to the state in both unweighted and weighted spaces in Section 3.1. The Lipschitz property of the nonlinear term is shown in Section 3.2, and the stability of the steady-state solution is proven in Section 3.3 and Section 3.4.
3.1. The Setting in the Model Case
Information about the stability of the steady state of system (5) is often disclosed by the information about the spectrum of the linear operator obtained by linearizing (5) with respect to the steady state. Therefore, we first define the linear differential expression in (8) by L:
We consider a differential operator associated with the differential expression L in the Sobolev space of vector-valued functions, and throughout we assume that .
Definition 1
([17]). In work on viscous conservation laws and related equations, a traveling wave is called spectrally stable in if the spectrum of is contained in and 0 is a simple eigenvalue of
As shown below, the essential spectrum of touches the imaginary axis. This prevents from being stable in the space , meaning that we have to replace this space by the weighted space , which has an exponential weight with respect to the variable z. In this new space, the nonlinearity loses the local Lipschitz property needed to determine the well-posedness of (8). To regain this, as in [10,11,12,15], we move on to the intersection space to perform further analysis.
Remark 2.
We first need information about the spectra of the linear operators associated with (19), which involves several operators in the different spaces considered below. We use the following notation for these operators. If B is a general system of n differential expressions, for instance, as in (19), then we use the notation and to denote the linear operator in and , respectively, as provided by the formula , with their natural domains. That is, for , we use to denote the linear operator provided by the formula , for which the domain is . We use to denote the operator in provided by the formula , for which the domain is the set of , where . We use the notation to denote the linear operator provided by , with the domain of being the set of satisfying , where and are the respective domains defined above.
First, we use Fourier transform to explore the spectrum of the constant coefficient differential operator on and the spectrum of the constant coefficient differential operator on , respectively. We use the following elementary proposition to show that the spectrum of on touches the imaginary axis and that the spectrum of on is away from the imaginary axis.
Proposition 1.
Assume that and are the constant coefficient linear differential operators associated with the differential expression L in (19). On the unweighted space for all integers , we have
meaninf that the spectrum of touches the imaginary axis. By choosing , we have
for some , meaning that the spectrum of is shifted to the left of the imaginary axis on the weighted space .
Furthermore, there exists such that for .
Proof.
By Lemma 1, as proved below, it is enough to consider the case , that is, to assume that . To find in the unweighted space , we can use Fourier transform. From the properties of the Fourier transform (see, e.g., [18], Section 6.5), the operator on is similar to the operator on when multiplying by the matrix-valued function
where . Thus, the spectrum of on is the closure of the union over of the spectra of the matrices . Hence, the spectrum of is equal to the closure of the set of for which there exists such that
This is a collection of curves , where are the eigenvalues of the matrices ; thus, the spectrum of the operator is
This implies that the spectrum of in touches the imaginary axis when .
We now need on the weighted space . First, we define the linear map provided by ; note that, by definition, N is an isomorphism of on . In particular, we can define a linear operator on with the domain , as maps in . As the operator is similar to on , it has the same spectrum.
In particular, let us consider the operator on with
Fix any when is considered in and . Then, temporarily re-denoting , we have
Denoting , ; a similar computation shows that for each
we have
Via Fourier transform, the operator on is similar to the operator of multiplication on by the matrix-valued function
where . Hence,
Then,
Thus, we conclude that for , we have , meaning that the spectrum on the weighted space is moved to the left of the imaginary axis.
Furthermore, the operator associated with the differential expression L in (19) generates an analytic semigroup provided that , and a strongly continuous semigroup provided that . As shown in [10], in either case enjoys the spectral mapping property, that is, the boundary of the spectrum of the semigroup operator is controlled by the boundary of the spectrum of the semigroup generator for any . Then, by the above-mentioned semigroup property (see, e.g., [10] Proposition 4.3), there exists such that □
Lemma 1.
Proof.
To show that the spectrum of in is the same as the spectrum of , we let denote the Fourier transform acting from into , where is the weighted -space with the standard weight . By the standard property of the Fourier transform, we have and . Thus, for a matrix-valued function obtained from (19) by replacing by and by .
On the other hand, the operator of multiplication by is an isomorphism of onto . Let us denote by the operator associated with L on the space and by the operator associated with L on the space . Per the previous paragraph, we then have . Here and below we use a slight abbreviation of this notation; properly written, implies and for all .
We remark that the operator of multiplication by , on is similar to the operator of differentiation on via Fourier transform . This implies that with the same matrix-valued function M as above. It follows that
therefore, the spectrum of on is the same as the spectrum of on , as the operators on and are similar.
By analogous argument, the spectrum of on is the same as the spectrum of on . □
Remark 3.
Recall that we denote . Let be the operator provided by the differential expression , where the domain of on is the set of u such that . We denote by and respectively the operators provided by the differential expression acting on unweighted and weighted spaces. The operator on can be written as . We have yet another approach to prove Propositon 1 using [16] (Volume IV, Theorem XIII.34, Theorem XIII.35, and Corollary 1). Indeed, because and are the generators of bounded semigroups on and , respectively, we have the following (see [16], Volume IV):
Thus, . It is easy to see that the spectrum of on is the non-negative semiline , and the spectrum of on satisfies for some ; thus, Proposition 1 is proven. Moreover, the same argument shows that if Γ is the curve that bounds the spectrum of on the right, then is the entire solid part of the plane bounded by Γ. We use Figure 1 to illustrate the spectrum of the linear operator on different spaces; in the weighted space, the spectrum is away from the imaginary axis and the operator extends in a semiline to negative infinity at each point on the original spectrum.
Figure 1.
(a) spectrum of the operator on , the red curve corresponds to the operator , while the blue curve corresponds to the operator ; (b) spectrum of the operator on ; (c) spectrum of the operator on .
Let
and for let be the operator on defined by (with the domain of being ) for .
Lemma 2.
Consider the operators and on defined by the differential expressions and provided in (26) and (27).
- (1)
- The operator generates a bounded strongly continuous semigroup on;
- (2)
- The operator satisfies on ;
- (3)
- The following is true on :
- (a)
- ;
- (b)
- There exist and such that for the strongly continuous semigroup we have for all .
Proof.
As in Lemma 1, we can prove that the operators , have the same spectrum on and on .
Using the Fourier transform, we find that the spectrum of on is the union of the curves for all . Thus, on , which proves (3)(a). Per the proof of Proposition A.1(1) in [11], the operator generates a bounded semigroup on . The operators on and associated with the same constant–coefficient differential expression are similar (see (23)); therefore, the semigroup they generate are similar, and (1) is proved.
The spectrum of on is the union of the curves for all ; therefore, on , and per Lemma 1 on as well, proving (2).
The assertion of (3)(b) is a direct consequence of (2); see [11] (Lemma 3.13). □
3.2. Nonlinear Terms in the Model Case
In this subsection, we study the nonlinear terms defined in (7) and prove that the nonlinearity is locally Lipschitz on the intersection space .
To obtain the Lipschitz property of the nonliner term on the multidimensional spaces and , we need to use space as defined in Equation (9).
It is convenient to write as follows:
where and is defined as in (2).
The proofs below are based on the fact that Sobolev embedding yields the inequality
for ; see [19] (Theorem 4.39). We begin with a few elementary facts.
Lemma 3.
Assume that and consider . Then, the following assertions hold.
- (1)
- If u, , then , and there exists a constant such that .
- (2)
- If u, , then , and there exists a constant such that .
- (3)
- If u, , then , and there exists a constant such that .
Proof.
Assertion (1) is in fact the Sobolev embedding inequality (30). Assertion (2) can be proven using (30), as
To show (3), let . Then, per (1),
and per (2),
Therefore, and . □
The nonlinearities of type (29) are a combination of the Nemytskij-type operator and multiplication operator by . In what follows, we need to establish both their local Lipschitz properties and more general operators of the type , where is a given function and . One-dimensional results of this kind can be found in [11] (Proposition 7.2). We present an analogue of the proof of [11] (Proposition 7.2)t in [15] (Appendix A); see Lemma 4 below.
Lemma 4.
Assume and let be a function from . Consider the formula
where , , , and the variable .
By dropping q from Lemma 4, we record the following corollary that can be used to study the components of the map from (29).
Corollary 1.
Let , and let and be defined accordingly. If and , then the formula
defines mappings from to and from to . The first is locally Lipschitz on any set with the form , while the second is locally Lipschitz on any set with the form .
Proposition 2.
- (1)
- defines a mapping from to that is locally Lipschitz on any set with the form.
- (2)
- defines a mapping from to that is locally Lipschitz on any set with the form.
Proof.
It can be shown that is a smooth bounded function. Let
then, is a smooth and bounded function. By applying Corollary 1 to the components of the vector-valued map H, we finish the proof. □
Proposition 3.
- (1)
- If , then there exists a constant such thaton any set with the form .
- (2)
- If , then there exists a constant such thaton any set with the form .
Proof.
Note that
Because is a smooth function, from Corollary 1 we have
Note that and , because and are components of the vector . Then, (1) holds, because
Similarly, using the fact that , we have
thus,
and (2) is proved. □
3.3. Stability of the Steady State of the Planar Front in the Model Case
In this subsection, we prove the stability of the end state of (5). From Propositions 1 and 2, we know that with initial data there is a unique mild solution to system (8) defined for , where (see, e.g., [20], Theorem 6.1.4). The set is open in , and the map from this set to is continuous (see, e.g., [21], Theorem 46.4). We summarize these facts as follows.
Proposition 4.
Let with . Then, for each , if , there exists depending on γ and δ with , such that the following is true. If satisfies
and , the solution of (8) is defined and satisfies
We can then prove the following proposition to show that is exponentially decaying in the weighted norm when is small in . We first establish the exponential decay of the solutions of (8) on .
Proposition 5.
Proof.
Because is a mild solution of (8) on , this satisfies the integral equation
Because by assumption , by Proposition 3 it is clear that is in , thus, we have
Next, we replace by in (35) and choose such that
for some and close to 1. Then, per Proposition 1 there exists such that for all .
Choosing any , for any such that , if , per Proposition 4 we can say that for all .
With the aid of Propostion 3 (1), there exists a constant depending on such that, for , when it follows that
For each and , if , then for all . Again, per Proposition 4,
Applying Gronwall’s inequality for the function , we can find that the inequality
implies, by Gronwall’s inequality, that
By choosing , we can conclude that (34) holds for any . □
On the unweighted space , we can rewrite system (8) as follows:
where . Using Propositions 2 and 3, we conclude that defines a mapping from to that is locally Lipschitz on any set with the form and Therefore, we obtain the following estimate.
Proposition 6.
Proof.
We note that is the solution of (36) and (37) with initial values at , that is . With the help of Proposition 3 (2), we can find a constant , meaning that
and
when . The solution of (37) in can be written as
Then, we choose some and such that
By Lemma 2 (3), there exists such that . For each and , if ,
Following Proposition 4, we obtain the following estimate for using (37):
We then calculate
By applying Gronwall’s inequality to , we infer that
Let ; then, for it follows that
which proves (39). Next, we proceed to prove (38). The solution of (36) in satisfies
First, because generates a bounded semigroup, per Lemma 2 (1) there exists a constant such that . Using (40) and the fact that
for , we infer that
Furthermore, using the fact that , for a constant independent of we have
3.4. Proof of Theorem 1
In this subsection, we present the main proof of the stability of the end state of (5) in . The proof relies on the following bootstrap argument based on Propositions 4–6. These propositions yield the existence of constants and , meaning that for every and every there exists such that for every the inequalities
hold for the solution of (8) with the initial value as long as . Next, we show that for each there is an such that, if , then for all . Assume ; without loss of generality, by setting and assuming , then by (41). Thus, the solution with the initial value ) again satisfies (41) for per Propositions 4 and 5. Thus, these propositions can be applied for all which proves its stability. As long as these propositions are applicable, we are able obtain more refined information about the behavior of the solution, including its boundedness in the -norm and the exponential decay in the -norm; see items (3)–(5) of Theorem 1.
With an initial value , let be the solution of (8) in , which we have already shown to exist on at least a short time period. We now complete the proof of the nonlinear stability of the end state by obtaining a control on solutions for all times t. For this, we need to use the following general result (see [22] Proposition 1.21):
Lemma 5
(Abstract Bootstrap Principle). First, let I be a time interval; then, suppose that for each we have two statements, a “hypothesis” and a “conclusion” . Suppose that we can verify the following four assertions:
- (a)
- (Hypothesis implies conclusion): If is true for some time , then is true for that time T.
- (b)
- (Conclusion is stronger than hypothesis): If is true for some time , then is true for all in a neighborhood of T.
- (c)
- (Conclusion is closed): If is a sequence of times in I which converges to another time , and is true for all , then is true.
- (d)
- (Base case): Of is true for at least one time , then is true for all .
We now state the main result in Theorem 1. The small constant in the proof can be taken as , where is chosen as in Proposition 6.
Theorem 1.
Let with and consider the semilinear system (8). There exist constants , , and a small such that for each we can find η to satisfy such that, if , the following is true for the solution of (8) for all :
- (1)
- is defined in
- (2)
- (3)
- (4)
- (5)
- .
Proof.
Let I be the time interval .
Let in Lemma 5 be the following statement. For each in which is chosen as in Proposition 6, there exists such that if , then is defined and on the time interval for some , depending on and . Thus, property (d) of the bootstrap principle is proven by Proposition 4.
Let be the following statement. There exists such that properties (3)–(5) in Theorem 1 hold within the time interval .
Let and let , where C is a constant satisfying with and as in Propositions 5 and 6.
Let with be the initial value of (8). Now, . Choose as in Proposition 1; per Propositions 5 and 6, items (3), (4), and (5) hold for . Thus, property (a) of the bootstrap principle is proven.
Property (c) holds by the continuity of .
Now, we need to prove property (b) of the bootstrap principle. Let with ; for any , inequilities (3), (4), and (5) hold. Thus, by continuity of , we can conclude that
If we take as an initial value of system (8), it satisfies ; by applying Proposition 4 again, there exists such that for all we have
Then, is true for , and property (b) is proven.
Thus, we finish the proof of Theorem 1 using the bootstrap principle. □
4. Stability of the End States for a General System
In this section, we study a steady state solution to (4) with and its perturbation depending on the spatial variable .
Without loss of generality, we take . Information about the stability of the zero solution is encoded in the spectrum of the operator obtained by linearizing (4) with respect to zero:
where is the differential with respect to .
Let be the Sobolev spaces , and define the weight function
and the spaces and as before. Analogously to the model problem discussed in Section 3, we use to denote the operator defined on provided by the map , with the domain . We use to denote the operator defined on as provided by , with the domain being the set of u, where . Throughout, we impose the following assumptions on in (4).
Hypothesis 1.
- (a)
- In appropriate variables , we assume that for some constant matrix we have
- (b)
- The function f is from to .
If Hypothesis 1 holds, then and
where and are some matrix-valued functions of size and , respectively. Then, we can write
where each is a nonnegative diagonal matrix of size and for . Equation (4) now reads as follows:
If we linearize (46) at , then the constant–coefficient linear equation depends only on , as per Hypothesis 1 (a) can be obtained as follows:
We denote by the right-hand side of (47) and let be the operator defined on and provided by with the domain .
In addition, we linearize (45) at ; per by Hypothesis 1 (a), the respective constant–coefficient linear equation reads
We denote ; thus, . Let be the operator defined on , provided by , with the domain .
With the additional assumptions listed below, we show that the perturbations of the left end state that are initially small in both the unweighted norm and weighted norm remain small in the unweighted norm and decay exponentially in the weighted norm. In addition, the -component of the perturbation decays exponentially in the unweighted norm. Below, we use the following hypotheses about the spectrum of .
Hypothesis 2.
In addition to Hypothesis 1, we assume that there exists a constant such that on .
As in Section 3.1, let such that , denote and , and define the linear operators , where and , where . Then, the operator on the space can be represented as
Hypothesis 2 holds if there exists a constant such that on . Indeed, following Remark 3, we have
Note that the spectra of on and are equal, similar to Lemma 6; thus, it is apparent that if on , then Hypothesis 2 is satisfied for any .
Hypothesis 3.
In addition to Hypothesis 2, we assume the following:
- (1)
- The operator generates a bounded semigroup on the spaces and
- (2)
- The operator satisfies on and
Note that we have used the following lemmas in stating these hypotheses, by analogy to Lemma 1 in Section 3.1.
Lemma 6.
Proof.
Because is associated with the constant–coefficient differential expression L, we can use the same proof as in Lemma 1. □
We now rewrite Equation (4) for the perturbation of the end state in a form amenable to the subsequent analysis. We seek a solution to (4) of the form . Using this notation, satisfies
Note that
This is the semilinear equation for the perturbation we examine here. Throughout the rest of this section, we assume for and .
Proposition 7.
Assuming that Hypotheses 1–3 hold, the following are true. (1) There exists such that on the weighted space , the spectrum of is bounded away from the imaginary axis for some . In addition, there exists such that
(2) On the unweighted space , we have for some , and there exists such that for all .
Proof.
Statement (1) holds by Hypothesis 2 and Lemma 6, while Statement (2) follows from Hypothesis 3 and Lemma 6. □
The above Proposition 7 provides the spectral stability of the linear operator in the semilinear system (51). We next estimate the local Lipschitz property for the nonlinear terms , as in (51) for the weighted and unweighted norms.
Proposition 8.
- (1)
- If , then , and on any bounded neighborhood with the form there is a constant such that .
- (2)
- If , then , and on any bounded neighborhood with the form there is a constant such that .
- (3)
- The formula defines a mapping from to that is locally Lipschitz on any bounded neighborhood with the form in .
In this proof, we refer to Lemma 4 for the components of by dropping q from the lemma. Note that
By applying Lemma 4 to the components of the vector under the integral, the mapping is locally Lipschitz on sets with the form , satisfying
Thus, per Lemma 3 (1) and (52), we conclude that the nonlinearity satisfies
while per Lemma 3 (2) and (52), it satisfies
as well, thus proving (1) and (2). Next, we use the definition of and infer
With the information that we have now obtained, the spectrum of the linear operator of system (51) is stable in the weighted space and the nonlinear terms of system (51) under the weighted norm satisfy certain locally Lipchitz conditions. Next, we proceed as in the proof of Propostions 4–6 in Section 3 and use similar Bootstrap arguments as those used in the proof of Theorem 1 to finally obtain the following stability result.
Theorem 2.
With an initial value , let be the solution of (51) in with , and let and . Assuming Hypotheses 1–3, there exist constants and a small such that for each we can find such that, if , then the following is true for all :
- is defined in
- .
As the proof is identical to the proof of Theorem 1, we do not restate it here.
5. Conclusions and Future Work
In this paper, we have studied a class of reaction–diffusion systems usually associated with combustion problems. In particular, they are characterized by a special product triangle structure, that is, the linear operator obtained after linearization of the system with respect to the traveling front has a triangular structure (25) and the nonlinear reaction terms have a product structure. This structure is caused by the strong dependence of the reaction rate on the temperature, which is displayed as a cut-off from the source in terms of mathematical expression. Examples of other systems that possess this type of structure include the exothermic-endothermic chemical reaction
Here, is the temperature, is the quantity of exothermic reactant, and is the quantity of endothermic reactant. The parameters and are positive, and there are positive constants and such that for and for , as well as the gasless combustion
where if and if . In this system, u is the temperature, v is the concentration of unburned fuel, g is the unit reaction rate, and is a constant parameter.
For a reaction–diffusion system with this structure, we show that if the spectrum of the linear operator projected in one-dimensional space is touching the imaginary axis, a weight function and weighted space can be used to shift the spectrum of the linear operator to the left to obtain the spectral stability of the operator. On the other hand, we show that the nonlinear reaction term with the product form has the local Lipschitz property in the constructed weighted space. By combining these facts, the stability of the steady-state solution of the planar front can be obtained.
However, there are several problems involving this same subject that remain unsolved for the time being. For example, the linear operator obtained by linearizing the system with respect to the planar front has isolated singularities, and each of these isolated singularities extends an infinite semiline in the multidimensional space, as discussed in Remark 3. This which leads us to presuppose, as in [15], that the diffusion coefficients of different variables of the system are identical; interested readers may refer to [15] (Proposition 3.1) for a detailed discussion.
Author Contributions
Formal analysis, X.Y.; Investigation, X.Y.; writing—original draft preparation, X.Y.; writing—review and editing, Q.L.; supervision, Q.L.; project administration, Q.L.; funding acquisition, X.Y. and Q.L. All authors have read and agreed to the published version of the manuscript.
Funding
Research funding was provided by the National Natural Science Foundation of China [Young Scholar 11901468]; Xi’an Jiaotong-Liverpool University [KSF-E-35]; and the National Science Foundation [NSF-HRD 2112556].
Data Availability Statement
Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
Acknowledgments
The authors thank Y. Latushkin at the University of Missouri-Columbia, for providing research questions and ideas, and for all the help he gave us.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Zel’dovich, Y.B.; Barenblatt, G.I.; Librovich, V.B.; Makhviladze, G.M. The Mathematical Theory of Combustion and Explosions; Consultants Bureau: New York, NY, USA, 1985. [Google Scholar]
- Volpert, A.I.; Volpert, V.A.; Volpert, V.A. Traveling Wave Solutions of Parabolic Systems, Translations of Mathematical Monographs; AMS: Providence, RI, USA, 1994. [Google Scholar]
- Berestycki, H.; Nirenberg, L. Traneling front solutions of semilinear equations in n dimensions. In Frontiers in Pure and Applied Mathematics; North-Holland: Amsterdam, The Netherlands, 1991; pp. 31–41. [Google Scholar]
- Sandstede, B. Stability of travelling waves. In Handbook of Dynamical Systems; Fiedler, B., Ed.; Elsevier: Amsterdam, The Netherlands, 2002; Volume 2, pp. 983–1055. [Google Scholar]
- Sandstede, B.; Scheel, A. Essential instabilities of fronts: Bifurcation, and bifurcation failure. Dyn. Syst. 2001, 16, 1–28. [Google Scholar] [CrossRef][Green Version]
- Henry, D. Geometric Theory of Semilinear Parabolic Equations; Lecture Notes in Mathematics; Springer: New York, NY, USA, 1981; Volume 840. [Google Scholar]
- Kapitula, T.; Promislow, K. An Introduction to Spectral and Dynamical Stability; Springer: New York, NY, USA, 2014. [Google Scholar]
- Pego, R.L.; Weinstein, M.I. Asymptotic stability of solitary waves. Comm. Math. Phys. 1994, 164, 305–349. [Google Scholar] [CrossRef]
- Ghazaryan, A. Nonlinear stability of high Lewis number combustion fronts. Indiana Univ. Math. J. 2009, 58, 181–212. [Google Scholar]
- Ghazaryan, A.; Latushkin, Y.; Schecter, S.; de Souza, A. Stability of gasless combustion fronts in one-dimensional solids. Arch. Ration. Mech. Anal. 2010, 198, 981–1030. [Google Scholar] [CrossRef]
- Ghazaryan, A.; Latushkin, Y.; Schecter, S. Stability of traveling waves for a class of reaction-diffusion systems that arise in chemical reaction models. SIAM J. Math. Anal. 2010, 42, 2434–2472. [Google Scholar] [CrossRef][Green Version]
- Ghazaryan, A.; Latushkin, Y.; Schecter, S. Stability of traveling waves for degenerate systems of reaction diffusion equations. Indiana University Math. J. 2011, 60, 443–472. [Google Scholar] [CrossRef]
- Ghazaryan, A.; Latushkin, Y.; Schecter, S. Stability of traveling waves in partly hyperbolic systems. Math. Model. Nat. Phenom. 2013, 8, 32–48. [Google Scholar]
- Latushkin, Y.; Schnaubelt, R.; Yang, X. Stable foliations near a traveling front for reaction diffusion systems. Discrete Cont. Dyn.-B 2017, 22, 3145–3165. [Google Scholar] [CrossRef][Green Version]
- Ghazaryan, A.; Latushkin, Y.; Yang, X. Stability of a planar front in a class of reaction-diffusion systems. SIAM J. Math. Anal. 2018, 50, 5569–5615. [Google Scholar] [CrossRef]
- Reed, M.; Simon, B. Methods of Modern Mathematical Physics, Analysis of Operators; Academic Press: New York, NY, USA, 1978. [Google Scholar]
- Freistühler, H.; Szmolyan, P. Spectral stability of small shock waves. Arch. Ration. Mech. Anal. 2002, 164, 287–309. [Google Scholar] [CrossRef]
- Engel, K.-J.; Nagel, R. One-Parameter Semigroups for Linear Evolution Equations; Springer: New York, NY, USA, 1999. [Google Scholar]
- Adams, R.A.; Fournier, J.F. Sobolev Spaces, 2nd ed.; Academic Press: New York, NY, USA, 2003. [Google Scholar]
- Pazy, P. Semigroups of Linear Operators and Applications to Partial Differential Equations; Springer: New York, NY, USA, 1983. [Google Scholar]
- Sell, G.; You, Y. Dynamics of Evolutionary Equations; Applied Mathematical Sciences; Springer: New York, NY, USA, 2002; Volume 143. [Google Scholar]
- Tao, T. Nonlinear Dispersive Equations: Local and Global Analysis, CBMS Regional Series in Mathematics; AMS: Providence, RI, USA, 2006. [Google Scholar]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).