
Let R be a commutative ring with multiplicative identity, C a coassociative and counital R-coalgebra, B an R-bialgebra. A clean comodule is a generalization and dualization of a clean module. An R-module M is called a clean module if the endomorphism ring of M over R (denoted by EndR(M)) is clean. Thus, any element of EndR(M) can be expressed as a sum of a unit and an idempotent element of EndR(M). Moreover, for a right C-comodule M, the endomorphism set of C-comodule M denoted by EndC(M) is a subring of EndR(M). A C-comodule M is a clean comodule if the EndC(M) is a clean ring. A Hopf module M over B is a B-module and a B-comodule that satisfies the compatible conditions. This paper considers the notions of a clean ring, clean module, clean coalgebra, and clean comodule in relation to the Hopf Module. We divide our discussion into two parts, i.e., clean and bi-clean Hopf modules. A B-Hopf module M is said to be clean if the endomorphism ring of M is clean, and M is a bi-clean Hopf module if M is clean as a module over B and also clean as a comodule over B. Moreover, we give sufficient conditions of (bi)-clean bialgebras and Hopf modules related to the cleanness concept of modules and comodules.
Citation: Nikken Prima Puspita, Indah Emilia Wijayanti. Bi-clean and clean Hopf modules[J]. AIMS Mathematics, 2022, 7(10): 18784-18792. doi: 10.3934/math.20221033
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Let R be a commutative ring with multiplicative identity, C a coassociative and counital R-coalgebra, B an R-bialgebra. A clean comodule is a generalization and dualization of a clean module. An R-module M is called a clean module if the endomorphism ring of M over R (denoted by EndR(M)) is clean. Thus, any element of EndR(M) can be expressed as a sum of a unit and an idempotent element of EndR(M). Moreover, for a right C-comodule M, the endomorphism set of C-comodule M denoted by EndC(M) is a subring of EndR(M). A C-comodule M is a clean comodule if the EndC(M) is a clean ring. A Hopf module M over B is a B-module and a B-comodule that satisfies the compatible conditions. This paper considers the notions of a clean ring, clean module, clean coalgebra, and clean comodule in relation to the Hopf Module. We divide our discussion into two parts, i.e., clean and bi-clean Hopf modules. A B-Hopf module M is said to be clean if the endomorphism ring of M is clean, and M is a bi-clean Hopf module if M is clean as a module over B and also clean as a comodule over B. Moreover, we give sufficient conditions of (bi)-clean bialgebras and Hopf modules related to the cleanness concept of modules and comodules.
Mathematical equations that contain two or more independent variables are called partial differential equations. They are found in various scientific applications, such as chemistry, physics, engineering and mathematics, which is why researchers have developed many techniques to solve such equations as homotopy perturbation method, variation iteration method, Adomian decomposition method and others [1,2,3,4,5,6,7,8,9].
Fractional calculus is a generalization of regular calculus, that calculates derivatives of functions of non-integer orders. Many definitions of fractional derivatives have been presented in the literature such as Riemann Louville, Caputo, conformable and others [10,11,12,13,14,15]. Furthermore, using each of these definitions can be viewed as a generalization of the normal calculus. For this reason, applying either of these definitions allows us to generalize our research to normal calculus, and since Caputo's fractional derivative is one of the most popular definitions, we establish our new results in terms of Caputo's fractional definition in this article. There are a number of different methods that mathematicians have used to solve ordinary and partial differential equations and systems in fractional calculus. One of these methods is the power series method, because it can solve such problems. On the other hand, there are too many methods that depend on the idea of power series, such as residual power series method [16,17,18,19,20,21,22,23,24,25,26], and some other techniques that combine the power series idea with transformations just as Laplace transform, ARA-transform, formable transform and others [27,28,29,30,31,32,33,34,35,36,37] to construct new ones. However, all these methods, introduce the solution in a convergent series form, but the difference lies in the level of difficulty during the applications.
The direct power series method (DPSM) used in this work was first introduced in [38], transformations are unnecessary, no limits or differentiations are required, this method only focuses on finding the nth coefficients of the series expansion of the analytic solution.
In DPSM we find the solution by computing a general term of the nth coefficients without going back to the hole power series every time we want to compute new coefficients. For this reason, DPSM helps mathematicians to find the approximate solutions better and faster. This method only takes two steps to write the general solution of some equations or systems that can be solved with other power series methods. At the end of the second step, we have a general form of the solution, expressed as an infinite series, and this makes it easier to find too many new coefficients of the series solution with computer programs. Furthermore, some different illustrative examples are presented in the fourth chapter and solved with the proposed method. We show that DPSM could be used to solve different types of problems and systems.
This paper is organized as follows, in the next section, we introduce some preparatory explanations on fractional operators, Section 3 introduces the methodology and the basic idea of DPSM and finally we consider some different examples on fractional partial differential equations and systems.
In this section we introduce the definition of the fractional Caputo and some theorems about power series.
Definition 2.1. If ψ(χ,τ) is a function of two variables and n is any natural number, then Caputo fractional partial derivative of order α with respect to τ is denoted and defined as
Dατψ(χ,τ)={1Γ(n−α)∫τ0(τ−t)n−α−1∂n∂τnψ(χ,τ)dt,n−1<α<n,∂n∂τnψ(χ,τ),n=α, | (2.1) |
where n∈N.
It is worth noting here that Caputo fractional partial derivative has the memory property. For more details and properties, see [39,40,41].
Lemma 2.1. [10,11]. Let ϱ(χ) be a real valued continuous function and α,τ>0. Then the following properties of Caputo's derivative are hold:
1) Dατϱ(χ)=0.
2) Dατ(τβϱ(χ))=Γ(β+1)Γ(β+1−α)τβ−αϱ(χ).
3) Dkατ(τnαϱ(χ))={Γ(nα+1)Γ((n−k)α+1)τ(n−k)αϱ(χ),n≥k,0n<k.
4) Dkατ(∑∞n=0ϱn(χ)(γτ)nαΓ(nα+1))=∑∞n=0γ(n+k)αϱn+k(χ)τnαΓ(nα+1).
Definition 2.2. [22] For any α such that, r−1<α≤r, r∈N a power series of the form:
∑∞n=0ϱn(χ)(τ−τ0)nαΓ(nα+1)=ϱ0(χ)+ϱ1(χ)(τ−τ0)αΓ(α+1)+ϱ2(χ)(τ−τ0)2αΓ(2α+1)+…, | (2.2) |
is called the multiple fractional power series about τ=τ0, where τ is a variable and ϱn(χ),∀n=0,1,⋯ are functions of χ called the coefficients of the series.
Theorem 2.1. [22,23] Suppose that ψ(χ,τ) has a fractional power series representation at τ=0, of the form:
ψ(χ,τ)=∑∞n=0ϱn(χ)τnαΓ(nα+1),α>0,χ∈I, | (2.3) |
where 0≤τ<R and Ris the radius of convergence. If Dnατψ(χ,τ) is continuous on (0,R), then, the coefficients ϱn(χ); ∀n=0,1,⋯, of the power series (2.3) are given by
ϱn(χ)=Dnατψ(χ,0). | (2.4) |
For the proof, see [22].
The convergence analysis of the presented power series are illustrated in the following theorem. We mention here, that these conditions are the required convergence conditions for DPSM [13].
Theorem 2.2. [35,36] Consider the fractional power series representation in (2.3), then we have the following cases:
a) If τ=0, the series representation (2.3) is convergent and the radius of convergence is R=0.
b) If τ≥0, the series representation (2.3) is convergent and the radius of convergence is R=∞.
c) If τ∈[0,R], the series representation (2.3) is convergent for some positive real number R and is divergent for τ>R, where R is the radius of convergence.
In the following arguments, we state some properties of the fractional power series (2.3):
1) The kth derivative of the fractional power series representation (2.3) is given by
Dkχψ(χ,τ)=∑∞n=0ϱ(k)n(χ)τnαΓ(nα+1), | (2.5) |
and the coefficients of the equation ϱ(m)n(χ); ∀n=0,1,… are given by
ϱ(k)n(χ)=Dkχ(Dnατψ(χ,0)). | (2.6) |
2) If we have {ψi(χ,τ)}mi=1 a sequence of functions of two variables, that has a power series expansion as follows:
ψi(χ,τ)=∑∞n=0ϱin(χ)τnαΓ(nα+1), | (2.7) |
then the coefficients of τnαΓ(nα+1) of ∏mi=1ψi(χ,τ) can be written by the following summation:
∏mi=1ψi(χ,τ)=∑j1,j2,…jm;j1+j2+⋯+jm=nϱ1j1(χ)ϱ2j2(χ)…ϱmjm(χ)Γ(nα+1)Γ(j1α+1)Γ(j2α+1)…Γ(jmα+1)τnαΓ(nα+1). | (2.8) |
In this section we present the main idea of the DPSM for solving time fractional partial differential equations (TFPDEs). We illustrate the technique of using DPSM to solve TFPDEs.
Assume that ψ(χ,τ) can be presented in the series representation (2.3). Consider the FPDE,
L[ψ(χ,τ)]+N[ψ(χ,τ)]=0, | (3.1) |
where L and N denote linear and nonlinear operators respectively of fractional or integer orders derivatives. Using DPSM we can get the solution of some cases-that will be considered in Theorem 3.1, below-of Eq (3.1) in a series representation which means, to find the values of the coefficients ϱn(χ) of the series expansion (2.3). The Caputo fractional derivative affects the series formula and changes the summation, so we need to illustrate the following theorem that study the effects of the fractional derivatives on the power series representations.
Theorem 3.1. [32] Suppose that ψ(χ,τ) and φ(χ,τ) have fractional power series representations such as:
ψ(χ,τ)=∑∞n=0ϱn(χ)τnαΓ(nα+1)andφ(χ,τ)=∑∞m=0ρm(χ)τmαΓ(mα+1), | (3.2) |
where ψ(χ,τ) and φ(χ,τ) are analytical functions, then we haveϱn(χ) and ρm(χ) are the coefficients of τnαΓ(nα+1)and τmαΓ(mα+1) in ψ(χ,τ) and φ(χ,τ) respectively,∀m=0,1,…, and n=0,1,⋯. Then we have:
a) ϱn+k(χ) is the coefficient for τnαΓ(nα+1) in the series expansion of Dkατψ(χ,τ) for any k=0,1,⋯.
b) γ(n+k)αϱn+k(χ) is the coefficient for τnαΓ(nα+1) in the series expansion of Dkατψ(χ,γτ) for any k=0,1,…, where γ∈R.
c) ∑ni=0ϱi(χ)ρn−i(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1) is the coefficient for τnαΓ(nα+1) in the series expansion of ψ(χ,τ)φ(χ,τ).
d) ∑ni=0βiαγ(n−i)αϱi(χ)ρn−i(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1) is the coefficient for τnαΓ(nα+1) in the series expansion of ψ(χ,βτ)φ(χ,γτ), where β and γ∈R.
e) ∑ni=0β(i+k)αγ(n−i+m)αϱi+k(χ)ρn−i+m(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1) is the coefficient for τnαΓ(nα+1) in the series expansion of Dkατψ(χ,βτ)Dsατφ(χ,γτ), where β, γ∈Randk,s=0,1,….
Proof. Substituting the series expansion of ψ(χ,τ) in Dkατψ(χ,τ),
Dkατψ(χ,τ)=Dkατ(∑∞n=0ϱn(χ)τnαΓ(nα+1)). | (3.3) |
Using part (4) of Lemma 2.1, we get
Dkατψ(χ,τ)=∑∞n=jϱn(χ)τ(n−k)αΓ((n−k)α+1). | (3.4) |
Thus, the series expansion can be written as
Dkατψ(χ,τ)=∑∞n=0ϱn+k(χ)τnαΓ(nα+1). | (3.5) |
Proof. Substituting the series expansion of ψ(χ,γτ)in Dkατψ(χ,γτ), we get
Dkατψ(χ,γτ)=Dkατ(∑∞n=0ϱn(χ)(γτ)nαΓ(nα+1)). | (3.6) |
Using part (4) of Lemma 2.1, we get
Dkατψ(χ,γτ)=∑∞n=jγnαϱn(χ)τ(n−k)αΓ((n−k)α+1). | (3.7) |
Thus, Eq (3.7), can be written as
Dkατψ(χ,γτ)=∑∞n=0γ(n+k)αϱn+k(χ)τnαΓ(nα+1). | (3.8) |
Proof. Multiplying the series expansion of ψ(χ,τ) and φ(χ,τ),
ψ(χ,τ)φ(χ,τ)=∑∞n=0ϱn(χ)τnαΓ(nα+1)∑∞m=0ρm(χ)τmαΓ(mα+1). | (3.9) |
Equation (3.9), can be simplified as
ψ(χ,τ)φ(χ,τ)=∑∞n=0∑∞m=0ϱn(χ)ρm(χ)τ(n+m)αΓ(nα+1)Γ(mα+1), | (3.10) |
which can be rewritten as
ψ(χ,τ)φ(χ,τ)=∑∞n=0(∑ni=0ϱi(χ)ρn−i(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1))τnαΓ(nα+1). | (3.11) |
Proof. Multiplying the series expansion of ψ(χ,βτ) and φ(χ,γτ),
ψ(χ,βτ)φ(χ,γτ)=(∑∞n=0ϱn(χ)(βτ)nαΓ(nα+1))(∑∞m=0ρm(χ)(γτ)mαΓ(mα+1)). | (3.12) |
Equation (3.12), can be written as
ψ(χ,βτ)φ(χ,γτ)=∑∞n=0∑∞m=0ϱn(χ)ρm(χ)βnαγmατ(n+m)αΓ(nα+1)Γ(mα+1), | (3.13) |
which can be simplified as
ψ(χ,βτ)φ(χ,γτ)=∑∞n=0(∑ni=0βiαγ(n−i)αϱi(χ)ρn−i(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1))τnαΓ(nα+1). | (3.14) |
Proof. Substituting the series expansion of ψ(χ,γτ) and φ(χ,γτ)in Dkατψ(χ,βτ)Dsατφ(χ,γτ), we get:
Dkατψ(χ,βτ)Dsατφ(χ,γτ),=Djαt(∑∞i=0ϱi(χ)(βτ)iαΓ(iα+1))Dmαt(∑∞j=0ρj(χ)(γτ)kαΓ(kα+1)). | (3.15) |
Using part (2) of Lemma 2.1, Eq (3.15) can be written as
Dkατψ(χ,βτ)Dsατφ(χ,γτ)=(∑∞n=0β(n+k)αϱn+k(χ)τnαΓ(nα+1))(∑∞m=0γ(m+s)αρm+s(χ)τmαΓ(mα+1)), | (3.16) |
which can be simplified as
Dkατψ(χ,βτ)Dsατφ(χ,γτ)=∑∞n=0∑∞m=0β(n+k)αγ(m+s)αϱn+k(χ)ρm+s(χ)τ(n+m)αΓ(nα+1)Γ(mα+1). | (3.17) |
Equation (3.17) can be written as
Dkατψ(χ,βτ)Dsατφ(χ,γτ)=∑∞n=0(∑ni=0β(i+k)αγ(n−i+m)αϱi+k(χ)ρn−i+m(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1))τnαΓ(nα+1). | (3.18) |
The proof is complete.
The main idea of DPSM depends on replacing each part of the target equation or system with its τnαΓ(nα+1) coefficients, in any equation that contains similar terms in Theorem 3.1, these replacements can be applied separately for each additive part, or if each part is multiplied by a real number. The main idea of the method is to do some replacements in the target equation and simplify the obtained series expansions in one series after simple computations, to get a general term of the coefficients in the series expansion (2.3) and hence, we get the analytic series solution of the equation by substituting n=1,2,…in the series form and so on.
Our goal in this section, is to explain the usage of DPSM in solving some TFPDEs and get numerical solutions for them. The method is basically, depends on assuming the series representation (2.3) of the solution and then find a general term of the series coefficients, that allows researchers to get better approximate solutions by getting many terms of the numerical solution they study.
The following steps illustrate the algorithm of DPSM in solving TFPDEs:
Step 3.1. Apply the replacements from Theorem 3.1 that is, replace each term of the target equation by its suitable similar coefficient ϱn(χ) of τnαΓ(nα+1).
Step 3.2. Simplify the obtained series representations from Step 3.1, and define a general form of the series solution by putting the higher index ϱn+k(χ) to the left-hand side and the rest of the coefficients into the right, to get a formula of the shape:
ϱn+k(χ)=ρ(an+k−1,an+k−2,…,a0). | (3.19) |
Step 3.3. Substitute the values of n, recursively from n=1,2,… as much as you need terms of the series solution.
In this section, some interesting examples on TFPDEs are solved, we clarify the steps of DPSM by solving fractional partial differential equations and system of fractional partial differential equations, each example is of different kind.
Example 4.1.[26] Consider the following temporal-fractional Burger equation of the form:
Dατψ(χ,τ)−ψχχ(χ,τ)+ψ(χ,τ)ψχ(χ,τ)=0,0<α≤1, | (4.1) |
subject to the initial condition,
ψ(χ,0)=2χ. | (4.2) |
Note that, when α=1 the exact solution of Eq (4.1) the integer case is
ψ(χ,τ)=2χ1+2τ. | (4.3) |
Solution 4.1. Applying the replacements of Theorem 3.1 on Eq (4.1), we get
Dατψ(χ,τ)↔ϱn+1(χ), |
ψχχ(χ,τ)⟷ϱ''n(χ), |
and
ψ(χ,τ)ψχ(χ,τ)⟷∑ni=0ϱi(χ)ϱ'n−i(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1). |
Substituting the new terms from the replacements into Eq (4.1), we get
ϱn+1(χ)−ϱ''n(χ)+∑ni=0ϱi(χ)ϱ'n−i(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1)=0. | (4.4) |
Then the Eq (4.1) can be expressed as
ϱn+1(χ)=ϱ''n(χ)−∑ni=0ϱi(χ)ϱ'n−i(χ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1). | (4.5) |
From the initial condition in (4.2),
for n=0, ϱ1(χ)=−4χ,
for n=1, ϱ2(χ)=16χ,
for n=2, ϱ3(χ)=−16χ(4+Γ(2α+1)Γ2(α+1)),
for n=3, ϱ4(χ)=64χ(4+Γ(2α+1)Γ2(α+1)+2Γ(3α+1)Γ(2α+1)Γ(α+1)),
for n=4, ϱ5(χ)=−256χ(4+Γ(2α+1)Γ2(α+1)+2Γ(3α+1)Γ(2α+1)Γ(α+1)+Γ(4α+1)Γ2(2α+1))−128χ(4+Γ(2α+1)Γ2(α+1))Γ(4α+1)Γ(3α+1)Γ(α+1), which are the same results obtained in [26]. DPSM save a lot of time in calculating the coefficients and the steps here are written completely.
Thus, the solution of Eqs (4.1) and (4.2), can be expressed as
ψ(χ,τ)=ϱ0(χ)+ταϱ1(χ)Γ(1+α)+τ2αϱ2(χ)Γ(1+2α)+τ3αϱ3(χ)Γ(1+3α)+τ4αϱ4(χ)Γ(1+4α)+τ5αϱ5(χ)Γ(1+5α) |
=2χ−4χταΓ(1+α)+16χτ2αΓ(1+2α)−16χ(4+Γ(2α+1)Γ2(α+1))τ3αΓ(1+3α) |
+64χ(4+Γ(2α+1)Γ2(α+1)+2Γ(3α+1)Γ(2α+1)Γ(α+1))τ4αΓ(1+4α) |
+(−256χ(4+Γ(2α+1)Γ2(α+1)+2Γ(3α+1)Γ(2α+1)Γ(α+1)+Γ(4α+1)Γ2(2α+1))−128χ(4+Γ(2α+1)Γ2(α+1))Γ(4α+1)Γ(3α+1)Γ(α+1))τ5αΓ(1+5α)+…. | (4.6) |
Substituting α=1we get
ψ(χ,τ)=2χ−4τχ+8τ2χ−16τ3χ+32τ4χ−64τ5χ+128τ6χ−… |
=2χ(1−2τ+4τ2−8τ3+16τ4−32τ5χ+64τ6χ−…), | (4.7) |
this result agrees, with the Maclaurin series of the exact solution of Eq (4.1) in the integer case, which is
ψ(χ,τ)=2χ1+2τ. | (4.8) |
The following figures illustrate some simulations of Example 4.1.
In Figure 1, we sketch the solution of Example 4.1 in 3D space with α=1. We compare the exact solution of the integer order case of Example 4.1 with the fifth approximate solution from DPSM and sketch the error in Figure 2. Figure 3 present the contour graphs of the solution with different values of α.
Example 4.2. [28] Consider the following time-fractional Phi-4 equation of the form:
D2ατψ(χ,τ)=ψχχ(χ,τ)−μ2ψ(χ,τ)−λψ3(χ,τ), | (4.9) |
with initial conditions,
ψ(χ,0)=√−μ2λtanh(μχ√12(ν2−1)), | (4.10) |
Dατψ(χ,0)=−μν√−μ2λ(ν2−1)sech2(μχ√12(ν2−1)), | (4.11) |
where ν is the speed of the traveling wave αϵ(0,1). The exact solution for α=1 is given by [28],
ψ(χ,τ)=√−μ2λtanh(μ(χ−vτ)√12(ν2−1)). | (4.12) |
Solution 4.2. The solution by DPSM can be obtained replacing each part of Eq (4.9) with its suitable coefficient of τnαΓ(nα+1) as in Theorem 3.1 to get the following:
ϱn+2(χ)=ϱ''n(χ)−μ2ϱn(χ)−λ∑i,j,ki+j+k=nϱi(χ)ϱj(χ)ϱk(χ)Γ((i+j+k)α+1)Γ(iα+1)Γ(jα+1)Γ(kα+1), | (4.13) |
from the initial conditions we have that ϱ0(χ)=ψ(χ,0) and ϱ1(χ)=Dατψ(χ,0).
For n=0,
ϱ2(χ)=ϱ''0(χ)−μ2ϱ0(χ)−λϱ30(χ) |
=λ(−μ2λ)3/2ν2Sech2(μ√1−1+ν2χ√2)Tanh(μ√1−1+ν2χ√2)−1+ν2. | (4.14) |
For n=1,
ϱ3(χ)=ϱ''1(χ)−μ2ϱ1(χ)−3λϱ1(χ)ϱ20(χ) |
=μ3ν3(−2+cosh(√2μ√1−1+ν2χ))sech4(μ√1−1+ν2χ√2)√−μλ(−1+ν2)√2(−1+ν2). | (4.15) |
For n=2,
ϱ4(χ)=ϱ''2(χ)−μ2ϱ2(χ)−3λϱ21(χ)ϱ0(χ)−3λϱ2(χ)ϱ20(χ) |
=12(ν2−1)2λ(ν2−1)λμν2(−μ2λ)3/2tanh(μ√1ν2−1χ√2)sech4(μ√1ν2−1χ√2) |
(2μλ(ν2−1)(ν2cosh(√2μ√1ν2−1χ)−2ν2−3)−3λ(ν2−1)2). | (4.16) |
For n=3,
ϱ5(χ)=ϱ''3(χ)−μ2ϱ3(χ)−λϱ31(χ)−6λϱ0(χ)ϱ1(χ)ϱ2(χ)−3λϱ3(χ)ϱ30(χ) |
=18√2(ν2−1)2μ3ν3(−μλ(ν2−1))3/2[sech7(μ√1ν2−1χ√2)μλ(ν2−1)48ν2√−μ2λsinh(μ√1ν2−1χ√2) |
−21ν2√−μ2λsinh(3μ√1ν2−1χ√2)+3ν2√−μ2λsinh(5μ√1ν2−1χ√2)−48√−μ2λsinh(μ√1ν2−1χ√2) |
+21√−μ2λsinh(3μ√1ν2−1χ√2)−3√−μ2λsinh(5μ√1ν2−1χ√2)+ν2(−cosh(5μ√1ν2−1χ√2)) |
+20(ν2+3)cosh(μ√1ν2−1χ√2)−(11ν2+39)cosh(3μ√1ν2−1χ√2) |
+3cosh(5μ√1ν2−1χ√2)+4λ(ν2−1)2cosh(μ√1ν2−1χ√2)], | (4.17) |
and then the 5th truncated series for ψ(χ,τ) can be expressed as,
ψ5(χ,τ)=ϱ0(χ)+ϱ1(χ)(τ−τ0)Γ(α+1)+∑5i=2ϱi(χ)(t−t0)iαΓ(iα+1) |
=√−μ2λtanh(μ√1ν2−1χ√2)−μνsech2(μ√1ν2−1χ√2)√−μλ(ν2−1)(τ−τ0)√2Γ(α+1) |
+λ(−μ2λ)3/2ν2sech2(μ√1ν2−1χ√2)tanh(μ√1ν2−1χ√2)(τ−τ0)2α(ν2−1)Γ(2α+1) |
−μ3ν3(cosh(√2μ√1ν2−1χ)−2)sech4(μ√1ν2−1χ√2)√−μλ(ν2−1)(τ−τ0)3α√2(ν2−1)Γ(3α+1) |
+λμ(−μ2λ)3/2ν2sech4(μ√1ν2−1χ√2)tanh(μ√1ν2−1χ√2)(2μ(cosh(√2μ√1ν2−1χ)ν2−2ν2−3)λ(ν2−1)−3λ(ν2−1)2)(τ−τ0)4α2(ν2−1)2Γ(4α+1)λ(ν2−1) |
+18√2(ν2−1)2Γ(5α+1)μ3ν3sech7(μ√1ν2−1χ√2)(−μλ(ν2−1))3/2[4λcosh(μ√1ν2−1χ√2)(ν2−1)2 |
+μ[−cosh(5μ√1ν2−1χ√2)ν2+48√−μ2λsinh(μ√1ν2−1χ√2)ν2−21√−μ2λsinh(3μ√1ν2−1χ√2)ν2 |
+3√−μ2λsinh(5μ√1ν2−1χ√2)ν2+20(ν2+3)cosh(μ√1ν2−1χ√2)−(11ν2+39)cosh(3μ√1ν2−1χ√2) |
+3cosh(5μ√1ν2−1χ√2)−48√−μ2λsinh(μ√1ν2−1χ√2)+21√−μ2λsinh(3μ√1ν2−1χ√2) |
−3√−μ2λsinh(5μ√1ν2−1χ√2)]λ(ν2−1)](τ−τ0)5α. | (4.18) |
We mention, that it's hard to find the fifth term by other analytical methods. By DPSM we can get many terms of the series solution by computer software.
In the following Figures 4 and 5, we sketch the exact solution of Example 4.2 in the integer case and compare it with approximate solution of fifth order in 2D and 3D. Also, we sketch the application solution in the 2D plane with different values of to show how the approximation solution converges to the exact solution of integer order.
Example 4.3. [22] The following form is considered:
Dατψ(χ,τ)+φχχ(χ,τ)+2(ψ2(χ,τ)+φ2(χ,τ))φ(χ,τ)=0, | (4.19) |
Dατφ(χ,τ)−ψχχ(χ,τ)−2(ψ2(χ,τ)+φ2(χ,τ))ψ(χ,τ)=0, | (4.20) |
with initial conditions,
ψ(χ,0)=cos(χ), | (4.21) |
φ(χ,0)=sin(χ). | (4.22) |
To find the general form of solutions by DPSM just do the replacements in Theorem 3.1 which could be directly written by,
ϱn+1(χ)=−ρ''n(χ)−2∑i,j,ki+j+k=n(ϱi(χ)ϱj(χ)ρk(χ)+ρi(χ)ρj(χ)ρk(χ))Γ(nα+1)Γ(iα+1)Γ(jα+1)Γ(kα+1), | (4.23) |
ρn+1(χ)=ϱ''n(χ)+2∑i,j,ki+j+k=n(ϱi(χ)ϱj(χ)ϱk(χ)+ρi(χ)ρj(χ)ϱk(χ))Γ(nα+1)Γ(iα+1)Γ(jα+1)Γ(kα+1). | (4.24) |
For n=0,
ϱ1(χ)=−δρ''0(χ)−γ(ϱ0(χ)ϱ0(χ)ρ0(χ)+ρ0(χ)ρ0(χ)ρ0(χ))−φ(χ)ρ0(χ)=−sinx, |
ρ1(χ)=δϱ''0(χ)+γ(ϱ0(χ)ϱ0(χ)ϱ0(χ)+ρ0(χ)ρ0(χ)ϱ0(χ))+φ(χ)ϱ0(χ)=cosx. |
For n=1,
ϱ2(χ)=−cosx, |
ρ2(χ)=−sinx. |
For n=2,
ϱ3(χ)=(5−2Γ(1+2α)Γ(1+α)2)sinx, |
ρ3(χ)=−(5−2Γ(1+2α)Γ(1+α)2)cosx. |
For n=3,
ϱ4(χ)=(5−2Γ(1+2α)Γ(1+α)2+4Γ(1+3α)Γ(1+α)Γ(1+2α)−2Γ(1+3α)Γ(1+α)3)cosx, |
ρ4(χ)=(5−2Γ(1+2α)Γ(1+α)2+4Γ(1+3α)Γ(1+α)Γ(1+2α)−2Γ(1+3α)Γ(1+α)3)sinx, |
which is the same general form of the solutions obtained in [22].
Example 4.4. [37] Consider the following time-fractional 3-dimentional Navier Stokes equation:
Dατψ1(χ,ς,ζ,τ)+ψ1(χ,ς,ζ,τ)∂ψ1(χ,ς,ζ,τ)∂χ+ψ2(χ,ς,ζ,τ)∂ψ1(χ,ς,ζ,τ)∂ς+ψ3(χ,ς,ζ,τ)∂ψ1(χ,ς,ζ,τ)∂ζ |
=υ(∂2ψ1(χ,ς,ζ,τ)∂χ2+∂2ψ1(χ,ς,ζ,τ)∂ς2+∂2ψ1(χ,ς,ζ,τ)∂ζ2), | (4.25) |
Dατψ2(χ,ς,ζ,τ)+ψ1(χ,ς,ζ,τ)∂ψ2(χ,ς,ζ,τ)∂χ+ψ2(χ,ς,ζ,τ)∂ψ2(χ,ς,ζ,τ)∂ς+ψ3(χ,ς,ζ,τ)∂ψ2(χ,ς,ζ,τ)∂ζ |
=υ(∂2ψ2(χ,ς,ζ,τ)∂χ2+∂2ψ2(χ,ς,ζ,τ)∂ς2+∂2ψ2(χ,ς,ζ,τ)∂ζ2), | (4.26) |
Dατψ3(χ,ς,ζ,τ)+ψ1(χ,ς,ζ,τ)∂ψ3(χ,ς,ζ,τ)∂χ+ψ2(χ,ς,ζ,τ)∂ψ3(χ,ς,ζ,τ)∂ς+ψ3(χ,ς,ζ,τ)∂ψ3(χ,ς,ζ,τ)∂ζ |
=υ(∂2ψ3(χ,ς,ζ,τ)∂χ2+∂2ψ3(χ,ς,ζ,τ)∂ς2+∂2ψ3(χ,ς,ζ,τ)∂ζ2), | (4.27) |
where φ∈R, and with the ICs,
ψ1(χ,ς,ζ,0)=−0.5χ+ς+ζ, | (4.28) |
ψ2(χ,ς,ζ,0)=χ−0.5ς+ζ, | (4.29) |
ψ3(χ,ς,ζ,0)=χ+ς−0.5ζ. | (4.30) |
The exact solution, when α=1, of the integer case is
ψ1(χ,ς,ζ,τ)=−0.5χ+ς+ζ−2.25χτ1−2.25τ2, |
ψ2(χ,ς,ζ,τ)=χ−0.5ς+ζ−2.25ςτ1−2.25τ2, |
ψ3(χ,ς,ζ,τ)=χ+ς−0.5ζ−2.25ζτ1−2.25τ2. |
Solution 4.3. The solution by DPSM can be obtained by replacing each part of Eqs (4.25)–(4.27) with its suitable coefficient of τnαΓ(nα+1) as in Theorem 3.1 to get the following relations:
ϱn+1(χ,ς,ζ)=−∑ni=0(ϱi(χ,ς,ζ)∂ϱn−i(χ,ς,ζ)∂χ+ρi(χ,ς,ζ)∂ϱn−i(χ,ς,ζ)∂ς+σi(χ,ς,ζ)∂ϱn−i(χ,ς,ζ)∂ζ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1) |
+υ(∂2ϱn(χ,ς,ζ)∂χ2+∂2ϱn(χ,ς,ζ)∂ς2+∂2ϱn(χ,ς,ζ)∂ζ2), |
ρn+1(χ,ς,ζ)=−∑ni=0(ϱi(χ,ς,ζ)∂ρn−i(χ,ς,ζ)∂χ+ρi∂ρn−i(χ,ς,ζ)ς+σi∂ρn−i(χ,ς,ζ)∂ζ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1) |
+υ(∂2ρn(χ,ς,ζ)∂χ2+∂2ρn(χ,ς,ζ)∂ς2+∂2ρn(χ,ς,ζ)∂ζ2), |
σn+1(χ,ς,ζ)=−∑ni=0(ϱi(χ,ς,ζ)∂σn−i(χ,ς,ζ)∂χ+σi∂σn−i(χ,ς,ζ)∂ς+σi∂σn−i(χ,ς,ζ)∂ζ)Γ(nα+1)Γ(iα+1)Γ((n−i)α+1) |
+υ(∂2σn(χ,ς,ζ)∂χ2+∂2σn(χ,ς,ζ)∂ς2+∂2σn∂ζ2). |
For n=0,
ϱ1=−ϱ0∂ϱ0∂χ−ρ0∂ϱ0∂ς−σ0∂ϱ0∂ζ+υ(∂2ϱ0∂χ2+∂2ϱ0∂ς2+∂2ϱ0∂ζ2) |
=−(−0.5χ+ς+ζ)(−0.5)−(χ−0.5ς+ζ)(1)−(χ+ς−0.5ζ)(1)=−2.25χ, |
ρ1=−ϱ0∂ρ0∂χ−ρ0∂ρ0∂ς−σ0∂ρ0∂ζ+υ(∂2ρ0∂χ2+∂2ρ0∂ς2+∂2ρ0∂ζ2) |
=−(−0.5χ+ς+ζ)(1)−(χ−0.5ς+ζ)(−0.5)−(χ+ς−0.5ζ)(1)=−2.25ς, |
σ1=−ϱ0∂σ0∂χ−ρ0∂σ0∂ς−σ0∂σ0∂ζ+υ(∂2σ0∂χ2+∂2σ0∂ς2+∂2σ0∂ζ2) |
=−(−0.5χ+ς+ζ)(1)−(χ−0.5ς+ζ)(1)−(χ+ς−0.5ζ)(−0.5)=−2.25ζ. |
For n=1,
ϱ2=−ϱ1∂ϱ0∂χ−ϱ0∂ϱ1∂χ−ρ1∂ϱ0∂ς−ρ0∂ϱ1∂ς−σ1∂ϱ0∂ζ−σ0∂ϱ1∂ζ+υ(∂2ϱ1∂χ2+∂2ϱ1∂ς2+∂2ϱ1∂ζ2) |
=−(−2.25χ)(−0.5)−(−0.5χ+ς+ζ)(−2.25)−(−2.25ς)(1)−(−2.25ζ)(1) |
=−2(0.5)(2.25)χ+2(2.25)ς+2(2.25)ζ=2(2.25)(−0.5χ+ς+ζ)=4.5ϱ0, |
ρ2=−ϱ1∂ρ0∂χ−ϱ0∂ρ1∂χ−ρ1∂ρ0∂ς−ρ0∂ρ1∂ς−σ1∂ρ0∂ζ−σ0∂ρ1∂ζ+υ(∂2ρ1∂χ2+∂2ρ1∂ς2+∂2ρ1∂ζ2) |
=2(2.25)χ−2(0.5)(2.25)ς+2(2.25)ζ=2(2.25)(χ−0.5ς+ζ)=4.5ρ0, |
σ2=−ϱ1∂σ0∂χ−ϱ0∂σ1∂χ−ρ1∂σ0∂ς−ρ0∂σ1∂ς−σ1∂σ0∂ζ−σ0∂σ1∂ζ+υ(∂2σ1∂χ2+∂2σ1∂ς2+∂2σ1∂ζ2) |
=2(2.25)χ+2(2.25)ς−2(0.5)(2.25)ζ=2(2.25)(χ+ς−0.5ζ)=4.5σ0, |
For n=2,
ϱ3=−(20.25+5.0625Γ(2α+1)Γ2(α+1))χ, |
ρ3=−(20.25+5.0625Γ(2α+1)Γ2(α+1))ς, |
σ3=−(20.25+5.0625Γ(2α+1)Γ2(α+1))ζ. |
For n=3,
ϱ4=(40.5+10.125Γ(2α+1)Γ2(α+1)+20.25Γ(3α+1)Γ(2α+1)Γ(α+1))(−0.5χ+ς+ζ), |
ρ4=(40.5+10.125Γ(2α+1)Γ2(α+1)+20.25Γ(3α+1)Γ(2α+1)Γ(α+1))(χ−0.5ς+ζ), |
σ4=(40.5+10.125Γ(2α+1)Γ2(α+1)+20.25Γ(3α+1)Γ(2α+1)Γ(α+1))(χ+ς−0.5ζ). |
So, the solution of systems (4.25)–(4.27) and (4.28)–(4.30) has the following series form:
ψ1(χ,ς,ζ,τ)=−0.5χ+ς+ζ−2.25Γ(1+α)χτα |
+2(2.25)Γ(1+2α)(−0.5χ+ς+ζ)τ2α−(2.25)2Γ(1+3α)(4+Γ(1+2α)Γ2(1+α))χτ3α |
+(2.25)2Γ(1+4α)(8+2Γ(1+2α)Γ2(1+α)+4Γ(1+3α)Γ(1+α)Γ(1+2α))(−0.5χ+ς+ζ)τ4α+⋯, | (4.31) |
ψ2(χ,ς,ζ,τ)=χ−0.5ς+ζ−2.25Γ(1+α)ςτα |
+2(2.25)Γ(1+2α)(χ−0.5ς+ζ)τ2α−(2.25)2Γ(1+3α)(4+Γ(1+2α)Γ2(1+α))ςτ3α |
+(2.25)2Γ(1+4α)(8+2Γ(1+2α)Γ2(1+α)+4Γ(1+3α)Γ(1+α)Γ(1+2α))(χ−0.5ς+ζ)τ4α+⋯, | (4.32) |
ψ3(χ,ς,ζ,τ)=χ+ς−0.5ζ−2.25Γ(1+α)ζτα |
+2(2.25)Γ(1+2α)(χ+ς−0.5ζ)τ2α−(2.25)2Γ(1+3α)(4+Γ(1+2α)Γ2(1+α))ζτ3α |
+(2.25)2Γ(1+4α)(8+2Γ(1+2α)Γ2(1+α)+4Γ(1+3α)Γ(1+α)Γ(1+2α))(χ+ς−0.5ζ)τ4α+⋯. | (4.33) |
The following figure (Figure 6) illustrates the graph of the exact solution of Example 4.3 and the 10th approximation solutions.
In several types of science like mathematics, physics, engineering statics, etc., there are massive numbers of equations and systems that need solutions. Mathematicians created and developed many analytical and numerical methods to find the solution accurately or approximately. Power series methods like residual power series, Laplace residual power series, and many others give exact solutions or sometimes provide approximate solutions that converge to the exact one. However, these methods require a lot of steps each time, especially for solving nonlinear equations and systems. In this paper, a new technique has been presented for the first time called the DPSM for solving TFPDEs. In the following, we mention some remarks on the new method
1) DPSM introduces an analytical series solution depending on the idea of power series representation.
2) The method is simple and applicable in presenting series solutions.
3) DPSM can obtain many terms of the series solution.
4) The proposed method, need no discretization, transformation differentiation or taking limit.
5) All numerical results obtained in this article by Mathematica 3.12.
This method is a simple method among all analytical methods. It depends on the idea of the power series expansion for solving time-fractional differential equations or systems. In the future, we attend to expand the replacements and solve integral equations.
The authors declare no conflicts of interest.
[1] |
W. K. Nicholson, Lifting idempotents and exchange rings, Trans. Amer. Math. Soc., 229 (1977), 269–278. https://doi.org/10.1090/S0002-9947-1977-0439876-2 doi: 10.1090/S0002-9947-1977-0439876-2
![]() |
[2] |
V. P. Camillo, D. Khurana, T. Y. Lam, W. K. Nicholson, Y. Zhou, Continuous modules are clean, J. Algebra, 304 (2006), 94–111. https://doi.org/10.1016/j.jalgebra.2006.06.032 doi: 10.1016/j.jalgebra.2006.06.032
![]() |
[3] | V. P. Camillo, D. Khurana, T. Y. Lam, W. K. Nicholson, Y. Zhou, A short proof that continuous modules are clean, In: Contemporary ring theory 2011, 2012,165–169. https://doi.org/10.1142/9789814397681_0015 |
[4] | M. E. Sweedler, Hopf algebra, Mathematics Lecture Note Series, New York: W. A. Benjamins, Inc., 1969. |
[5] | T. Brzeziński, R. Wisbauer, Corings and comodules, United Kingdom: Cambridge University Press, 2003. |
[6] |
N. P. Puspita, I. E. Wijayanti, B. Surodjo, Graded modules as a clean comodule, J. Math. Res., 12 (2020), 66–73. https://doi.org/10.5539/jmr.v12n6p66 doi: 10.5539/jmr.v12n6p66
![]() |
[7] |
N. P. Pusita, I. E. Wijayanti, B. Surodjo, Clean coalgebra and clean comodules from finitely generated projective modules, Algebra Discrete Math., 31 (2021), 251–260. http://dx.doi.org/10.12958/adm1415 doi: 10.12958/adm1415
![]() |
[8] | D. E. Radford, Hopf algebras, Series on Knots and Everything, Vol. 49, USA: World Scientific, 2011. https://doi.org/10.1142/8055 |
[9] | S. Montgomery, Hopf algebras and their actions on rings, In: CBMS regional conference series in mathematics, American Mathematical Society, 1993. |
[10] | J. Han, W. K. Nicholson, Extension of clean rings, Commun. Algebra, 29 (2001), 2589–2595. https://doi.org/10.1081/AGB-100002409 |
[11] | W. W. McGovern, Characterization of commutative clean rings, Int. J. Math. Game Theory Algebra, 15 (2006), 403–413. |
[12] | C. Natasescu, F. Oystaeyen, Methods of graded rings, Springer-Verlag Berlin Heidelberg, 2004. |
[13] |
N. P. Pusita, I. E. Wijayanti, B. Surodjo, Some properties of clean R-coalgebra C, AIP Conf. Proc., 2268 (2020), 040006. https://doi.org/10.1063/5.0017810 doi: 10.1063/5.0017810
![]() |
[14] |
D. D. Anderson, V. P. Camillo, Commutative rings whose element are a sum of a unit and idempotent, Commun. Algebra, 30 (2002), 3327–3336. https://doi.org/10.1081/AGB-120004490 doi: 10.1081/AGB-120004490
![]() |
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20. | Boyu Liu, Wenyan Wang, An efficient numerical scheme in reproducing kernel space for space fractional partial differential equations, 2024, 9, 2473-6988, 33286, 10.3934/math.20241588 | |
21. | Tao Liu, Runqi Xue, Bolin Ding, Davron A. Juraev, Behzad Nemati Saray, Fazlollah Soleymani, A Novel and Effective Scheme for Solving the Fractional Telegraph Problem via the Spectral Element Method, 2024, 8, 2504-3110, 711, 10.3390/fractalfract8120711 | |
22. | Raed M. Khalil, Rania Saadeh, Mohamed A. Abdoon, Mohammed Berir, Ahmad Qazza, Ali Elrashidi, 2024, Analyzing Chaotic Jerk System with Hyperbolic Sine: a new algorithm for Engineering Applications, 979-8-3315-4001-2, 1, 10.1109/ACIT62805.2024.10877120 | |
23. | Iqbal M. Batiha, Rania Saadeh, Iqbal H. Jebril, Ahmad Qazza, Abeer A. Al-Nana, Shaher Momani, Composite Fractional Trapezoidal Rule with Romberg Integration, 2024, 140, 1526-1506, 2729, 10.32604/cmes.2024.051588 |