1. Introduction
Fractional calculus is an effective tool to model the complex nonlinear phenomena (indicated as anomalous) arising in continuum mechanics, thermodynamics, medicine, biology and so on (see, for example, [
1,
2,
3,
4,
5,
6,
7,
8] and also references therein). Features of anomalous diffusion contain history dependence (memory term), long-range (or nonlocal) correlation in time and heavy-tail characteristics, while its signature is that the mean square displacement of the diffusion species
scales as a nonlinear power law in time, i.e.,
. If the
anomalous diffusion exponent belongs to the interval
, the underlying diffusion process is called subdiffusive. The constitutive relation of the viscoelastic material and the anomalous diffusion are successfully described by single-, multi-term or distributed order fractional ordinary or partial differential equations (
FODE or
FPDE) and by general integro-differential equations with a generalized fractional derivative:
where
is a non-negative locally integrable kernel.
Specifying the kernel
in (
1) gives rise to different types of fractional derivatives. In particular, the Caputo fractional derivative
of order
is recovered via (
1) for the power-law memory kernel
, with
being the Euler Gamma function. The distributed order memory kernel
where
is a non-negative weight function, reduces (
1) to the fractional derivative of the distributed order, and corresponding
FPDEs or
FODEs of a distributed order. An important particular case of such equations is the diffusion equation with multi-term time-fractional derivatives with respect to time
which is the main focus of this paper. Indeed, to reduce (
1) with (
2) to the multi-term fractional derivatives, the weight function in (
2) is taken in the form of a finite linear combination of the Dirac delta functions with non-negative weight coefficients.
It is worth noting that the order of the corresponding fractional differential equations is defined with
the anomalous diffusion exponent. In order to derive fractional differential equations from physical laws, one can exploit two different ways. The first approach is related to modeling continuous time random walk processes at the micro-level and taking a continuous limit at the macro-level [
9]. The second method is appealed to conservative laws and specific constitutive relations with memory [
1,
4,
10].
In this paper, motivated by the mathematical model for oxygen delivery through capillaries described in [
4,
5], we focus on the study of the initial-boundary value problem to semilinear diffusion equations with multi-term fractional derivatives, where some coefficients
may be non-negative.
Let
be a bounded domain with a smooth boundary
, and for any fixed
, denote
For
, we discuss the following non-autonomous multi-term subdiffusion equation with memory terms in the unknown function
,
supplemented with the initial condition
and subject to the Dirichlet boundary condition
(DBC)
where
,
,
,
f,
g and the memory kernel
are prescribed in
Section 3.
The symbol ∗ stands for the time-convolution product on
, i.e.,
while
denotes the Caputo fractional derivative of the order
with respect to time
t, defined as
There is an equivalent definition
if
u is an absolutely continuous function. As for operators
, they are the linear elliptic operators of the second order with time-dependent coefficients (written in divergence form), that is
where we put
For the mathematical treatment of single-term time-fractional diffusion equations with and without memory terms (i.e., subdiffusion equations similar to (
4) with
and either
or
), which have been extensively studied (analytically and numerically) for the last few decades, we refer the reader to [
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23]. The diffusion equation with the general integro-differential operator (
1) is analyzed in [
7,
8] (see also the references therein). The Cauchy problem for this equation on an unbounded space domain is discussed in [
24]. Exploiting the Fourier method, well-posedness and a maximum principle for the initial-boundary value problem to the subdiffusion equation with multi-term fractional derivatives (
3) with the positive constant coefficients
are studied in [
25]. In [
26], a solution to an initial-boundary value problem is formally represented by Fourier series and the multivariate Mittag–Leffler function. However, the authors do not provide the proof of the convergence of these series. This gap in the case of the multi-term time-fractional diffusion equation with positive constant coefficients
was filled in [
27]. Initial-boundary value problems to equations with operator (
3) where coefficients
(i.e.,
x- dependent) are discussed in [
28]. The semilinear equation with the general fractional derivative (
1) is analyzed in [
29], where the uniqueness and the local/global existence are proved by means of the Schauder fixed-point theorem. Finally, we quote [
3,
4,
5,
6,
30,
31], where some analytical and numerical solutions were constructed to the corresponding initial-boundary value problems to the evolution equation with the operator (
3).
The main distinction of equation (
4) from the equations in the aforementioned previous works is related to the multi-term fractional derivatives:
, which can be rewritten in the form of (
1) with the kernel
being either a negative function or a function alternating in sign. Indeed, choosing
and appealing to Lemma 4 in [
14], we end up with the equality
where the kernel
is
negative for
(
is the Euler–Mascheroni constant). It is worth noting that the non-negativity of the kernel
plays a crucial role in the previous investigations of
FPDEs and related initial/initial-boundary value problems. This assumption is removed in our research. Moreover, equation (
4) contains fractional derivatives calculated from the product of two functions: the desired solution
u and the prescribed coefficients
. The last peculiarity provides additional difficulties to study since the typical Leibniz rule does not work in the case of fractional derivatives, i.e.,
To the author’s best knowledge, there are only two papers [
32,
33] in the published literature addressing the solvability of initial-boundary value problems to the equation similar to (
4). Indeed, the first result concerning to existence and uniqueness of global classical solutions to the linear version (i.e.,
) of the non-autonomous equation (
4) with alternating in sign
and
subjected to various types of boundary conditions was presented in [
32]. However, solvability in the smooth classes (fractional Hölder spaces) requires stronger assumptions on the right-hand sides in the corresponding problems. Thus, our first goal of this art is to fill this gap, providing the well-posedness to the linear version of (
4)–(
6) under weaker requirements on the given functions. Namely, assuming that
belong to the proper fractional Sobolev spaces, we prove the one-to-one strong solvability in the class
,
of (
4)–(
6) with
. On this route, the main ingredient is a priori estimates in the fractional Sobolev spaces, which give rise to the Hölder regularity of a solution. Moreover, we establish similar results to the
—term fractional equations:
with
,
.
The second novelty of this paper is related to the well-posedness of the nonlinear Cauchy–Dirichlet problem (
4)–(
6), i.e.,
. Indeed, in [
33], this nonlinear model was analyzed in the case of a one-dimensional space domain and only time-dependent coefficients
Therefore, the second achievement of this art is the extension of the result of [
33] to the case of semilinear equation (
4) with coefficients
depending on the space and time variables and stated in a multidimensional domain
. It worth noting that, compared to [
33], the analyzed model in the multidimensional case will require
-regularity on the memory kernel
. Namely, if
g is locally Lipschitz, then the main point to study the global classical solvability is searching a priori estimates for the solution
u, and in turn the bound for
. In the one-dimensional case, the Sobolev embedding theorem provides the inequality
exploiting only the bound of
. This trick cannot be drawn in the multidimensional case, where bound (
7) is eventually reached via the following iterative inequalities:
To this end, we first rewrite equation (
4) in a suitable form, where the memory term does not contain the principal part of the operator
(i.e.,
). Then, we exploit the integral iterative technique from [
18]. At the same time, as a side effect, the term
appears in the equation. Here,
is the conjugate kernel, having the same properties of
. This explains the requirement of a smoother kernel in the multidimensional case.
Outline of the Paper
The paper is organized as follows: in
Section 2, we introduce the notation and the functional setting. The main assumptions are given in
Section 3. The principal results, Theorems 1–2 and Lemma 1, are stated in
Section 4. Theorem 1 is related to a priori estimates of the solution
u in
and in
in the case of the linear version of (
4)–(
6), while Theorem 2 concerns the global classical solvability of the corresponding nonlinear problem. The existence and the uniqueness of a strong solution to (
4)–(
6) with
are stated in Lemma 1. It is worth noting that this claim is a simple consequence of Theorem 1 and the results related to the one-to-one classical solvability established in our previous work [
32], so we give the proof of this lemma in
Section 3. Some definitions and some auxiliary results from fractional calculus, playing a key role in this art, are given in
Section 5. The proof of Theorem 1 is carried out in
Section 6. Here, exploiting so-called one variant of a Leibniz rule to Caputo derivatives,
and
, and following the approach from Section 5 in [
18], we rewrite equation (
4) in an appropriate form, where the principal part of the integro-differential operator
is represented as
; the leading part of the operator
(as we wrote above) is not involved in the memory term. After that, in
Section 6.1, we first obtain a priori estimates in the fractional Sobolev spaces for a small time interval and then discuss how these estimates can be extended to the whole time interval. In
Section 6.2, collecting the obtained estimates in the space
with results in [
23], we evaluate the Hölder seminorms of the solution
u. In particular, in the case of homogeneous initial and boundary conditions, this estimate reads as
Finally,
Section 7 is devoted to the verification of Theorem 2. The main tool in our arguments is the continuation method related to the study of a family of auxiliary problems depending on a parameter
. On this route, one has to obtain a priori estimates for the solutions which are independent of
(see
Section 7.1). The key bound is the estimate of
, produced via integral iteration techniques adapted to the case of multi-term fractional derivatives.
5. Technical Results
In this Section we present some properties of fractional derivatives and integrals as well as several technical results that will be used in this art. First, we begin with some definitions of fractional derivatives and integrals.
Throughout this work, for any
, we denote (as we wrote before)
and define the fractional Riemann–Liouville integral and the derivative of the order
, respectively, of a function
with respect to time
t as
where
is the ceiling function of
(i.e., the smallest integer is greater than or equal to
).
Clearly, for
we have
Therefore, the Caputo fractional derivative of the order
to a function
can be given as
if both derivatives exist (see (2.4.8) [
2]).
In the first proposition, which subsumes and partially generalizes (in particular, it concerns (iii) in the statement below) Propositions 4.1 and 4.2 from [
18], we remind the reader of some useful properties of fractional integrals and derivatives.
Proposition 1. The following relations hold.
- (i)
Let , . Then for any function , there is If, in addition, , and is any even integer, it is also true that - (ii)
Let θ be a positive number, and let be a bounded function on . Then - (iii)
Let , . Then the equality holds: - (iv)
For any given positive numbers and , the following equalities are fulfilled:
for any . The positive constant C depends only on T, and either if or if .
The next result describes the main properties of the function , where a kernel is completely monotonic and satisfies the following requirements.
H8. For any (including )
and all , there holdsMoreover, for some
and , the following inequalities are fulfilled: Clearly, the last inequality in H8 tells us that the kernel is a completely monotonic function.
Proposition 2. Let assumption H8 hold. Then, for any functions and satisfying requirementsandthe following relations hold: - (i)
- (ii)
For any integer even there is
If, in addition, is non-negative, then this bound holds for integer odd p.
Proof. First, we verify the point (i) of this assertion. It is worth noting that if
and
, this claim is proved in Lemma 1 [
11] for any fixed
. Here, we extend this result to the case of a more general kind of
.
By the definition of a derivative, we have
Then, taking advantage of the easily verified representation
we arrive at the equality
Finally, keeping in mind
H8 and the smoothness of the functions
and
, we end up with the desired equality.
Coming to the proof of point (ii) in this proposition, we first verify the cases of
and
. To this end, substituting
to the equality in (i) of this claim, we deduce the relations
Appealing to the complete monotonicity of
and to the non-negativity of the function
(if
), we immediately end up with the desired estimates for
. Finally, taking advantage of these estimates and exploiting the induction, we complete the proof of (ii) for
, and hence, the proof of Proposition 2. □
Introducing the new function
with
we assert the following claim:
Corollary 1. Let Then for any function , , and for each even integer , the inequalityholds for all . If additionally is non-negative, then this bound holds for any integer odd p. Proof. It is apparent that this statement is a simple consequence of Proposition 2 if
meets requirement
H8. In light of (
10) and (
12), the kernel
satisfies the first four conditions in
H8. Thus, we are left to check that
is completely monotonic for all
.
If
and
satisfy the assumption of this claim, then definitions of
and
provide the positivity of the function
for all
. Then, straightforward calculations arrive at the equality
Finally, appealing to the positivity of and bearing in mind the relation , we immediately obtain the non-negativity of the function . This finishes the proof of this corollary. □
The next assertion is related to the fractional differentiation of a product, the so-called one variant of the Leibniz rule in the case of fractional derivatives.
Corollary 2. Let and . For , we assume that
- (i)
either
- (ii)
or with .
Then the equalityholds, and has the regularity If, in addition, , then for any and all , the equality holdswith . Proof. First of all, we remark that under a stronger regularity on the function
, representation (
13) was proved in Corollary 3.1 [
37]. Here, we just extend this result to the case of a weaker assumption on the
. Namely, we require that
belongs to either
or
.
Appealing to the definition of the Caputo fractional derivative and taking into account the smoothness of functions
and
, we easily conclude that
After that, performing differentiation in the last integral arrives at the desired equality. Coming to the smoothness of the function
, it is a simple consequence of the obtained representation (
13) and the regularity of
and
.
Obviously, relation (
14) is a simple consequence of (
13) and (
11). Indeed, in virtue of
, we can rewrite (
13) as
Finally, computing the fractional integral
of both sides in this equality and taking into account Proposition 2.2 in [
2] and semigroup property to the fractional Riemann-Liouville integral, we end up with (
14). This completes the verification of this corollary. □
We now state and prove some inequalities that will be needed to prove estimate (
8) in
Section 6.2. First, we introduce the function
where
,
and
are some given functions whose smoothness provides the boundedness of the singular integral in (
15).
Lemma 2. Let arbitrarily fixed and . We assume that and . Then, there are the following inequalities:
- (i)
where is the positive constant in the Young inequality for a convolution (see [38]). - (ii)
where . - (iii)
If, for any and we additionally assume that and for all . Then, for any small , the estimates hold: Hereand is the constant in the Gagliardo–Nirenberg inequality.
Proof. The inequalities in point (i) are verified with straightforward calculations, where we exploit the Young inequality for a convolution and relations in (iv) of Proposition 1.
Concerning point (ii), this estimate is a simple consequence of the easily verified inequality
and the Young inequality for a convolution.
As for the verification of the first inequality in (iii), bearing in mind restrictions on
and appealing to the embedding Theorem (see (1.4.4.6) in [
35]), we conclude that
and
Collecting (
15), (
16) with the homogeneous initial data of
and (
15) allows us to apply Theorem 3.1 [
37] and deduce the equality
Next, taking advantage of this representation to compute
norm of
and performing standard technical calculations, we have
Finally, straightforward calculations and inequality (
16) arrive at the desired bound.
Consecutive application of formula (3.5.4) in [
2] to the difference
Young inequality for a convolution and, finally, the first inequality in (iii) of this claim provides the estimate
for any
. Finally, using this bound and the Young inequality to manage the term
, we arrive at the first estimate in (iii).
Coming to the second inequality in (iii), the Gagliardo–Nirenberg and Cauchy inequalities lead to the bound
for any
, which together with Jensen’s inequality to a sum, in turn, provides
After that, choosing
and applying (
17) to control the second term in the right-hand side of the inequality above, we immediately end up with
Finally, collecting this estimate with the first inequality in (i) yields the estimate in (iii). This completes the proof of Lemma 2. □
Remark 8. It is worth noting that repeating the arguments leading to the first bound in (iii) of Lemma 2 arrives at the following inequalities in the case of :with being defined in (ii) of Lemma 2. Finally, for convenience, we remind the reader of the result related to the global classical solvability of the linear problem corresponding to (
4)–(
6). The result, written as a lemma, is obtained in our previous work [
32] (see Theorem 4.1 there) and will be exploited in
Section 7 to prove the one-valued solvability of the nonlinear model (
4)–(
6).
Lemma 3. Let be any fixed, , , and let . We assume that assumptions H2–H5 hold. Then, linear equation (4) with the initial condition (5), subject to the Dirichlet boundary condition (6), has a unique classical solution in , possessing the regularity . This solution fulfills the estimateThe generic constant C is independent of the right-hand sides of (4)–(6). 7. Proof of Theorem 2
Here, we proceed with a detailed proof of this Theorem in the case of homogeneous initial and boundary conditions, i.e., (
18). Indeed, to convert the general case to this special one, we take advantage of Remark 3.1 in [
18] and Lemma 3 to the linear model for the unknown function
,
and we obtain the existence of a unique solution
satisfying the bound
Here, we used assumption
H6 and Remark 3.1 [
18] to handle the term
.
Then, we search a solution of the original problem (
4)–(
6) in the form
where the unknown function
is a solution of the problem
Here, we set
Remark 9. Assumption (H6) and the estimates of v readily provide the following inequalities for the functions F and G:and for all and ,with Moreover, the straightforward calculations and the definition of the function v arrive at the equalities Hence, the last relations mean that the compatibility conditions hold in problem (
29).
As a result,
Theorem 2 should be proved only in the case of homogeneous initial and boundary conditions, i.e., for problem (29).To this end, we exploit the so-called continuation argument, similar to the case of subdiffusion equations with a single-term fractional derivative (i.e., if
and
) described in our previous work [
18]. This approach is related to the analysis of the family of problems for
:
Let (
30) be solvable on
for any
. Clearly, for
problems (
30) transform to the linear problem studied in [
32]. Thus, keeping in mind assumptions
H1–H5 and Remark 9, we can apply Lemma 3 to (
30) with
and deduce the global classical solvability in the corresponding classes. Therefore,
. Then, we have to check that the set
is open and closed at the same time. On this step, we use the essential arguments described in Section 5.3 [
18] (i.e., in the case of the equation with a single-term fractional derivative in time). Hence, in our consideration here, we restrict ourselves to a detailed description of only the differences in the proof, which emphasize the difficulties involved in the multi-term fractional derivatives (in general with a non-positive kernel
). We preliminarily observe that these peculiarities are related to producing a priori estimates for the solutions to (
30) in
and
, uniformly as
, and are stated in the following lemma. The proof of this claim is provided in
Section 7.1.
Lemma 4. Let the assumptions of Theorem 2 hold, and let be the solution to problems (30). Then for any there are the following estimates:The positive constant C is independent of λ and the right-hand sides of (30), and depends only on T and the structural parameters of the problem. Finally, exploiting Lemma 4 and Theorem 1 (in particular, the estimate
in (
8)) and recasting step-by-step the arguments of Section 5.2 in [
18], we complete the proof of Theorem 2.
Thus, we are left to verify statements in Lemma 4.
7.1. Proof of Lemma 4: Verification of Estimates in (31)
First, we remark that the second estimate in (
31) is verified with the standard Schauder technique and by means of Lemma 3, Remark 9 and the estimate of
in (
31). Hence, to prove Lemma 4, we are left to produce the first inequality in (
31). We proceed here with a detailed proof of this estimate in the case of the positive function
. This means that the second fractional derivative in time may have a negative kernel. Another case is simpler and is examined either in the similar manner or with arguments from Section 5.1 in [
18].
Here, contrary to the case of a single-term fractional derivative in time (see arguments in Lemma 5.2 [
18]) we first estimate the maximum of
in a small time interval. It is worth noting that, in the case of negative
, this estimate is obtained straight on the whole time interval
.
Namely, on the first step, exploiting the integral iteration technique adapted to the case of multi-term fractional derivatives, we obtain the bound
for each fixed
,
.
The second stage deals with the extension of (
32) to the whole time interval
.
Step 1: Estimates of . Recasting the arguments of
Step 1 of
Section 6.1 leading to representation (
19), we rewrite the equation in (
30) in the form
where we set
while
are defined in (
19). Collecting equalities (
11) (where
) and (
12) with assumption
H7, we deduce that
Then, taking into account this equality and multiplying (
33) by
with
and then integrating over
, we arrive at the inequality (after standard technical calculations with appealing to
H2)
To handle the first two terms in the left-hand side of this estimate, we use Corollary 1 and statement (i) in Proposition 1, respectively, and we deduce
Then, taking into account the definition of
, Proposition 2.2 in [
2] and keeping in mind (
14), we compute the fractional integral
of both sides in this inequality. Hence, we end up with
where
We recall that
At this point, we evaluate each term , separately.
• It is worth noting that, the terms
are examined with arguments leading to (5.8), (5.10) and (5.11) in [
18]. Thus, taking into account Remark 9 and assumptions
H2, H3, H7, we immediately achieve the estimate
• As for
and
, we pre-observe that the bound of
is the same as the one of
. Applying the Young inequality to the function
and then collecting Proposition 1 with the smoothness of
,
and
, we end up with
where the positive constant
C depends only on
T,
,
,
and the corresponding norms of
and
.
• By assumption
H7, we immediately conclude that
In particular, the last inequality arrives at the estimate
Now, collecting the estimates of
with the relation
we conclude that
In order to evaluate the integral
, we appeal to the first interpolation inequality in Proposition 4.6 [
18] with
. Hence, we have
Exploiting the Gronwall inequality (see Proposition 4.3 [
18]) arrives at
for any
, where we set
while
is the classical Mittag–Leffler function of the order
(see its definition in (2.2.4) [
39]).
After that, applying this estimate to handle the last term in the right-hand side of (
35) and then taking into account formula (3.7.44) in [
39] to compute the fractional integral of the Mittag–Leffler function, we obtain
At last, denoting
with
, we derive the bound
At this point, we discuss two possibilities:
- (i)
either ,
- (ii)
or .
Clearly, in the case (i), passing to the limit as
in (
36), we end up with the desired estimate. Conversely, if (ii) holds, then
and letting
and having in mind the convergence of the series, we deduce that
Finally, to control the term
, we first put
in (34) and then apply the Gronwall inequality (4.3) in [
18] (where we set
). As a result, taking into account assumption
H2, we end up with the desired estimate (
32) and, hence, the second inequality in (
31) for each
.
Step 2: Extension of estimate (32) to the whole time interval. To this end, we modify the arguments of
Step 2 in
Section 6.1. Indeed, setting there (see (
23) and (
24))
we designate
as a solution of the linear problem
Thanks to (
32) and (
31) with
, we have
with the constant
C being independent of
and
.
Then, appealing to relations (
38), we apply Theorem 4.1 in [
32] to problem (
37) and end up with the one-valued classical solvability of this problem such that
After that, we introduce new unknown function
satisfying relations
where we set
By virtue of (
38) and (
39), we deduce that
Moreover, the estimate
holds, and
has the properties of
(see Remark 9).
At last, introducing new variable
and performing the change of variable in (
40) (that is similar to
Step 2 in
Section 6.1), and then recasting the arguments of
Step 1 in this subsection, we arrive at estimate (
31) for
. Finally, repeating this procedure a finite number of times, we exhaust the entire
, which proves estimate (
31) if
for any fixed
.