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. 2023 Apr 29;9(5):e15891. doi: 10.1016/j.heliyon.2023.e15891

Modified conformable double Laplace–Sumudu approach with applications

Shams A Ahmed a,b, Rania Saadeh c,, Ahmad Qazza c, Tarig M Elzaki d
PMCID: PMC10165409  PMID: 37168890

Abstract

In this study, we combine two novel methods, the conformable double Laplace-Sumudu transform (CDLST) and the modified decomposition technique. We use the new approach called conformable double Laplace-Sumudu modified decomposition (CDLSMD) method, to solve some nonlinear fractional partial differential equations. We present the essential properties of the CDLST and produce new results. Furthermore, five interesting examples are discussed and analyzed to show the efficiency and applicability of the presented method. The results obtained show the strength of the proposed method in solving different types of problems.

Keywords: Laplace transform, Sumudu transform, Conformable derivative, Double laplace– sumudu transform, Decomposition method

1. Introduction

Fractional partial differential equations have recently been shown to be crucial for describing a wide range of phenomena and applications in science and engineering, including fluid dynamics, electrical circuits, optics, physics, and others [[1], [2], [3], [4], [5], [6], [7], [8], [9], [10]]. In the literature, a number of definitions of fractional integrals and derivatives, including those by Caputo, Hadamard, and others, have been explored [[11], [12], [13], [14], [15], [16], [17]]. For instance, the quotient and product rules [[18], [19], [20], [21], [22], [23]] are among the features of the ordinary derivatives that are not always met by fractional derivatives. A novel definition of a conformable fractional derivative, which virtually meets most of the standard features of derivatives, was proposed by the researchers in Ref. [[24], [25]].

Numerous mathematicians and authors have created new methods to solve conformal differential problems, including the simplest method [26], Kudryashov method [27], double Shehu transform [28], Tanh method [29,30], reliable methods [31], double Sumudu transform [32,33], conformable Laplace transform (CLT) method [34,35], conformable double Laplace transform method [36], and conformable Sumudu transform (CST) method and others [[37], [38], [39], [40], [41], [42], [43], [44]].

The double Laplace-Sumudu transformation method, a unique approach to double transformations, has been introduced recently and has been successfully used to solve families of fractional partial differential equations [[45], [46], [47], [48]]. Unfortunately, this integral transformation cannot directly handle nonlinear equations, unlike other integral transformations. Because of this, mathematicians have developed new techniques that incorporate integral transformations with numerical methods like the decomposition method, the perturbation method, the iteration variation method, and others [[49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59]].

In this study, we introduce a unique method for numerically solving nonlinear conformable fractional differential equations, known as the CDLSMD method. The approach is effective in producing approximate series solutions that converge. With no evidence of noise terms, the approach suggested in this work quickly converges the obtained series solutions. While the components of the series solutions are represented by other analysis techniques, such as the homotopy perturbation approach and the Adomian decomposition method, these terms should also have noise terms [60].

Following that, we introduce a nonlinear conformable partial differential equation that is given by

bnγynγ(ψ(xηη,yγγ))+cmηxmη(ψ(xηη,yγγ))+N[ψ(xηη,yγγ)]=g(xηη,yγγ),xηη,yγγ>0,0<γ,η1,m,nN, (1)

with (1), we associate the initial conditions

jγψ(xηη,0)yjγ=fj(xηη),j=0,1,...,n1, (2)

and the conditions

kηψ(0,yγγ)xkη=hk(yγγ),k=0,1,...,m1. (3)

here , c are constants, N is the nonlinear operator, and g(xηη,yγγ) is a given function that can be expressed as g(xηη,yγγ)=g1(xηη,yγγ)+g2(xηη,yγγ).

In this work, we introduce the CDLSMD method to investigate certain applications similar to those in (1) connected to conditions (2) and (3). The modified decomposition method [[60], [61], [62], [63], [64]] and the CDLST method are combined in the CDLSMD approach. Contrary to other analysis approaches, abandoning the CDLST approach along with the modified decomposition method enables for quick convergence to the exact solutions without discretization or linearization, as shown in Ref. [60]. This study's major objective is to propose the CDLSMD approach for investigating how conformal nonlinear partial differential equations are solved.

The research presents the fundamental definitions and facts of the CDLST, then the key concept of the novel technique, and lastly the solution to certain numerical applications to demonstrate the effectiveness and adaptability of the proposed approach.

2. Fractional derivatives

Definition 1

[24]. Given ψ:(0,)R, then the CFD (conformable fractional derivative) of order γ of ψ is defined by

dγdyγψ(y)=limσ0ψ(y+σy1γ)ψ(y)σ,y>0,σ(0,1].

Definition 2

[44] Given ψ(xηη,yγγ):R+×R+R, then the conformable fractional partial derivatives (CFPDs) of order η and γ of the function ψ(xηη,yγγ) is defined by

ηxηψ(xηη,yγγ)=limρ0ψ(xηη+ρx1η,yγγ)ψ(xηη,yγγ)ρ,
γyγ(xηη,yγγ)=limσ0ψ(xηη,yγγ+σy1γ)ψ(xηη,yγγ)σ,

where xηη,yγγ>0,0<η,γ1, ηxη and γyγ denote the η and γ fractional derivatives respectively.

Definition 3

Let <γm+1, m=0,1,2,, and set α=γm then the conformable fractional integral (CFI), starting a of order γ of ψ(y) is defined by

(Iγa)ψ(y)=1m!ay(yτ)m(τa)α1ψ(τ)dτ,

where ψ(τ) is continuous

The following theorems present some results related to partial derivatives the conformable partial fractional derivatives, as follows.

Theorem 4

[39]. suppose 0<η,γ1 and ψ(xηη,yγγ) be a differentiable at a point xηη,yγγ>0, then

ηxηψ(xηη,yγγ)=xη+1ψ(xηη,yγγ)x.
γyγψ(xηη,yγγ)=yγ+1ψ(xηη,yγγ)y. (4)

Proof. We find, from the definition 1,

ηxηψ(xηη,yγγ)=limρ0ψ(xηη+ρX1η,yγγ)ψ(xηη,yγγ)ρ,

putting ρx1η=θ.

ηxηψ(xηη,yγγ)=limθ0ψ(xηη+θ,yγγ)ψ(xηη,yγγ)θxη1=xη+1limθ0ψ(xηη+θ,yγγ)ψ(xηη,yγγ)θ=xη+1ψ(xηη,yγγ)x

By similar arguments, we prove (4).

Theorem 5

Suppose 0<η,γ1 and c,d,m1,m2,δ, and εR; then

ηxη(cψ(xηη,yγγ)+dζ(xηη,yγγ))=cηxηψ(xηη,yγγ)+dηxηζ(xηη,yγγ),
ηxη(eδxηη+εyγγ)=δeδxηη+εyγγ,
γyγ(eδxηη+εyγγ)=εeδxηη+εyγγ,
ηxη(xηη)m1(yγγ)m2=m1(xηη)m11(yγγ)m2,
γyγ(xηη)m1(yγγ)m2=m2(xηη)m1(yγγ)m21,
ηxη(sin(xηη)sin(yγγ))=cos(xηη)sin(yγγ),
γyγ(sin(xηη)sin(yγγ))=sin(xηη)cos(yγγ).

The proof can be obtained using Theorem 4.

3. Basic facts of the CDLST

Definition 6

[65] Assume that ψ(xηη,yγγ),xηη,yγγR+ and 0<η,γ1 is a function of two variables. Then,

  • (i)

    The fractional conformable Laplace transform of ψ(xηη) order η, denoted by Lxη[ψ(xηη)]=Ψη(υ) and defined as

Lxη[ψ(xηη)]=Ψη(υ)=0eυxηηψ(xηη)xη1dx,x>0.
  • (ii)

    The conformable fractional Sumudu transform of ψ(yγγ) order γ, denoted by Syγ[ψ(yγγ)]=Ψγ(ω) and defined as

Syγ[ψ(yγγ)]=Ψγ(ω)=1ω0e1ωyγγψ(yγγ)yγγγ1dy,y>0.
  • (iii)

    The CDLST of ψ(xηη,yγγ), denoted by LxηSyγ[ψ(xηη,yγγ)]=Ψη,γ(υ,ω) and defined as

LxηSyγ[ψ(xηη,yγγ)]=Ψη,γ(υ,ω)=1ω00eυxηη1ωyγγψ(xηη,yγγ)xη1yγ1dxdy,

where υ,ωC are Laplace – Sumudu variables of yηη,xγγand0<γ,η1

The inverse CDLST Lx1Sy1[Ψη,γ(υ,ω)]=ψ(xηη,yγγ) is defined by

Lx1Sy1[Ψη,γ(υ,ω)]=ψ(xηη,yγγ)=12πiαiα+ieυxηη(12πiβiβ+i1ωeyγωγΨη,γ(υ,ω)dω)dυ.

The usual double Laplace –Sumudu transform and the CDLST are related by the following theorem.

Theorem 7

Suppose thatc,dRand0<γ,η1, then the followings hold:

  • 1.

    LxηSyγ[c]=LxSy[c]=cυ,υ>0

  • 2.

    LxηSyγ[(xηη)m(yγγ)n]=LxSy[(x)m(y)n]=m!n!ωnυm+1, where m and n are positive integral.

  • 3.

    LxηSyγ[ecxηη+dyγγ]=LxSy[ecx+dy]=1(υc)(1dω)

  • 4.

    LxηSyγ[sin(cxηη)sin(dyγγ)]=LxSy[sin(cx)sin(dy)]=c(υ2+c2)dω1+d2ω2

  • 5.

    First shifting property for CDLST:

IfLxηSyγ[ψ(xηη,yγγ)]=Ψη,γ(υ,ω), then

LxηSyγ[ecxηη+dyγγψ(xηη,yγγ)]=11dωΨη,γ(υc,ω1dω).
  • 6.

    Second shifting property for the CDLST:

  • IfLxηSyγ[ψ(xηη,yγγ)]=Ψη,γ(υ,ω), then

LxηSyγ[ψ(xηηδηη,yγγεγγ)H(xηηδηη,yγγεγγ)]=eυδηη1ωεγγΨη,γ(υ,ω),

whereH(xηηδηη,yγγεγγ)={1,xηη>δηη,yγγ>εγγ0,otherwise

Proof. For the proof, see [[45], [46], [47], [48]].

Now we discuss the conditions for the existence of the CDLST.

If ψ is of the exponential orders c and; (xηη,yγγ)(,) and if there exist a nonnegative real number K:xηη>X,yγγ>Y;

then:

|ψ(xηη,yγγ)|=Kecxηη+dyγγ,

and we write:

ψ(xηη,yγγ)=O(ecxηη+dyγγ)as(xηη,yγγ)(,)

or,

lim(xηη,yγγ)(,)eυxηη1ωyγγ|ψ(xηη,yγγ)|=Klim(xηη,yγγ)(,)e(υc)xηη(1ωd)yγγ=0,
υ>c,1ω>d.

Then, the function ψ is of exponential order as (xηη,yγγ)(,)

Theorem 8

Assume that the function ψ defined on the interval (0,X) and (0,Y) of the exponential orders c and d, then CDLST of ψ exists for all υ and 1ω supplied Re[υ]>c and Re[1ω]>d.

Proof. We find, from the Definition 6 (iii),

|Ψη,γ(υ,ω)|=|1ω00eυxηη1ωyγγψ(xηη,yγγ)dxdy|K0e(υc)xηηdx01ωe(1ωd)yγγdy=K(υc)(1dω),Re[υ]>c,Re[1ω]>d (5)

Thus, from Equation (5) we've got,

lim(xηη,yγγ)(,).|Ψ(υ,ω)|=0,orlim(xηη,yγγ)(,).Ψ(υ,ω)=0.

Theorem 9

If

LxηSyγ[ψ(xηη,yγγ)]=Ψη,γ(υ,ω)=Ψ(υ,ω),

then the CDLST of the conformable partial derivatives of orders η and γ can be represented as follows: 0<γ,η1.

LxηSyγ[ηxη(ψ(xηη,yγγ))]=υΨ(υ,ω)Ψ(0,ω). (6)
LxηSyγ[γyγ(ψ(xηη,yγγ))]=ω1Ψ(υ,ω)ω1Ψ(υ,0). (7)
LxηSyγ[2ηx2η(ψ(xηη,yγγ))]=υ2Ψ(υ,ω)υΨ(0,ω)Ψx(0,ω). (8)
LxηSyγ[2γy2γ(ψ(xηη,yγγ))]=ω2Ψ(υ,ω)ω2Ψ(υ,0)ω1Ψy(υ,0). (9)
Proof of (6)
LxηSyγ[ηxη(ψ(xηη,yγγ))]=1ω00eυxηη1ωyγγηψxηxη1yγ1dxdy=1ω0e1ωxγγyγ1(0eυxηηηψxηxη1dx)dy. (10)

Since we have Theorem 4, ηψxη=xη+1ψx. we use this result into Equation (10).

Therefore, Equation (10) becomes

LxηSyγ[ηxη(ψ(xηη,yγγ))]=1ω00eυxηη1ωyγγηψxηxη1yγ1dxdy=1ω0e1ωyγγyγ1(0eυxηηψxdx)dy. (11)

Considering

0eυxηηψxdx=ψ(0,y)+υΨ(υ,y) (12)

Substituting (12) in (11) with simple calculations, we get the result (6), as follows

LxηSyγ[ηyη(ψ(xηη,yγγ))]=υΨ(υ,ω)Ψ(0,ω).

The remaining results in(7), (8), (9)can be proved by similar arguments.

Additionally, the previous findings can be generalized I the following formulas.

LxηSyγ[mηxmη(ψ(xηη,yγγ))]=υmΨ(υ,ω)k=0m1υm1kSyγ[kηxkη(ψ(0,yγγ))], (13)
LxηSyγ[nγynγ(ψ(xηη,yγγ))]=ωnΨ(υ,ω)j=0n1ωn+jLxη[jγyjγ(ψ(xηη,0))]. (14)

The proof of(13), (14)can be obtained by mathematical induction.

4. Idea of CDLST combined with modified decomposition technique

In this part, we exercised CDLST joined to the modified decomposition approach to find the solutions to nonlinear conformable fractional equations as below.

Applying CDLST on Equation (1), we get

b(ωnΨ(υ,ω)j=0n1ωn+jLxη[jγψ(xηη,0)yjγ])+c(υmΨ(υ,ω)k=0m1υm1kSyγ[kηψ(0,yγγ)ykη])+LxηSyγ[N[ψ(xηη,yγγ)]]=G1(υ,ω)+LxηSyγ[g2(xηη,yγγ)]. (15)

Operating the CLT and CST for conditions (2) and (3), we get,

Lxη[jγψ(xηη,0)yjγ]=Fj(υ),j=0,1,,n1,
Syγ[kηψ(0,yγγ)xkη]=Hk(ω),k=0,1,...,m1. (16)

By substituting (16) for (15), we have

b(ωnΨ(υ,ω)j=0n1ωn+jFj(υ))+c(υmΨ(υ,ω)k=0m1υm1kHk(ω))=G1(υ,ω)+LxηSyγ[g2(xηη,yγγ)N[ψ(xηη,yγγ)]]. (17)

Simplifying Equation (17), we obtain

Ψ(υ,ω)=[bωn+cυm]1(b(j=0n1ωn+jFj(υ))+c(k=0m1υm1kHk(ω))+G1(υ,ω))+(bωn+cυm)1LxηSyγ[g2(xηη,yγγ)N[ψ(xηη,yγγ)]] (18)

Taking (Lxη)1(Syγ)1 of (18), we get

ψ(xηη,yγγ)=(Lxη)1(Syγ)1[[bωn+cυm]1(b(j=0n1ωn+jFj(υ))+c(k=0m1υm1kHk(ω))+G1(υ,ω))]+(Lxη)1(Syγ)1[(bωn+cυm)1LxηSyγ[g2(xηη,yγγ)N[ψ(xηη,yγγ)]]]. (19)

Now, use the modified decomposition approach by assuming

ψ(xηη,yγγ)=i=0ψi(xηη,yγγ) (20)

By decomposing the nonlinear term as:

N[ψ(xηη,yγγ)]=i=0Ai, (21)

for some Adomian polynomials Ai(ψ) that are given by:

Ai(ψ0,ψ1,ψ2,...,ψn)=1i!didλi(N[i=0λiψi])λ=0,i=0,1,2,.

Substituting Equation (20) and Equation (21) in Equation (19), we get:

i=0ψi(xηη,yγγ)=(Lxη)1(Syγ)1[(bωn+cυm)1(b(j=0n1ωn+jFj(υ))+c(k=0m1υm1kHk(ω))+G1(υ,ω))+(Lxη)1(Syγ)1[[bωn+cυm]1LxηSyγ[g2(xηη,yγγ)i=0Ai]]].

As result, the following recurrence relations are obtained

ψ0(xηη,yγγ)=(Lxη)1(Syγ)1[(bωn+cυm)1(b(j=0n1ωn+jFj(υ))+c(k=0m1υm1kHk(ω))+G1(υ,ω))], (22)
ψ1(xηη,yγγ)=(Lxη)1(Syγ)1[(bωn+cυm)1LxηSyγ[g2(xηη,yγγ)A0]], (23)
ψs+1(xηη,yγγ)=(Lxη)1(Syγ)1[(bωn+cυm)1LxηSyγ[As]],s1. (24)

Following that, one can get the solution of (1)

ψ(xηη,yγγ)=ψ0(xηη,yγγ)+ψ1(xηη,yγγ)+ψ2(xηη,yγγ)+....

5. Numerical applications

To assess the effectiveness and usefulness of the CDLSMD approach, numerous applications of nonlinear fractional partial differential equations are discussed in this section.

Example 4.1

Let us dicuss the dissipative wave equation of conformable derivative as:

2γψy2γ2ψx2+y(ψψx)=2eyγγsinxηη2e2yγγsinxηηcosxηη,0<γ1 (25)

with initial conditions:

ψ(xηη,0)=sinxηη,ψy(xηη,0)=sinxηη, (26)

and BCs:

ψ(0,yγγ)=0,ψx(0,yγγ)=eyγγ. (27)

Solution. Using the CDLST to (25) and the CLT to (26) and CST to (27), to get,

Ψ(υ,ω)=1(υ2+1)(1+ω)ω21υ2ω2LxηSyγ[2e2yγγsinxηηcosxηη+y(ψψx)]. (28)

Taking (Lxη)1(Syγ)1[Ψ(υ,ω)] of (28), we get

ψ(xηη,yγγ)=eyγγsinxηη(Lxη)1(Syγ)1[ω21υ2ω2LxηSyγ[2e2yγγsinxηηcosxηη+y(ψψx)]]. (29)

Following that, operating the modified decomposition approach and substituting (20) in (29) and utilizing the outcomes in (22), (23), (24), we get the components of the solution as:

ψ0(xηη,yγγ)=eyγγsinxηη,
ψ1(xηη,yγγ)=(Lxη)1(Syγ)1[ω21υ2ω2LxηSyγ[2e2yγγsinxηηcosxηη+A0]]=0,A0=y(ψ0(ψ0)x),
ψ2(xηη,yγγ)=(Lxη)1(Syγ)1[ω21υ2ω2LxηSyγ[A1]]=0,A1=y(ψ1ψ0x+ψ0ψ1x).

Thus, we obtain the accurate solution of Equation (25) as:

ψ(xηη,yγγ)=eyγγsinxηη, (30)

and putting η=γ=1; we have the exact solution as,

ψ(x,y)=eysinx.

In the following figures, we sketch the 3D plots of the accurate solution of Equation (25) in Fig. 1 (a), which is the same approximate obtained solution, when putting η=γ=1. In Fig. 1 (b), we sketch the approximate solution with various values of η and γ: η=γ=1,0.9,0.8.

In Table 1 below, we introduce the absolute exact errors obtained from computing the absolute difference of the exact and CDLSMD solutions obtained in this example with different values of the variables y=0.1,0.2,0.3 at x=1.

Example 4.2

The KdV equation of conformable derivative is given by:

γψyγψψx+3ψx3=exηη(yγγ+1)+yγγexηη(yγγexηη+1),0<γ1 (31)

with initial condition:

ψ(xηη,0)=1. (32)

and boundary conditions:

ψ(0,yγγ)=1yγγ,ψx(0,yγγ)=ψxx(0,yγγ)=yγγ. (33)

Solution. Applying the CDLST on (31) and CLT to (32) and the CST to (33), to get

Ψ(υ,ω)=1υωυ1+ω1+ωυ3LxηSyγ[yγγexηη(yγγexηη+1)+ψψx]. (34)

Taking (Lxη)1(Syγ)1[Ψ(υ,ω)] of (34), we get

ψ(xηη,yγγ)=1yγγexηη+(Lxη)1(Syγ)1[ω1+ωυ3LxηSyγ[yγγexηη(yγγexηη+1)+ψψx]]. (35)

Using the modified decomposition technique, and substituting (20) in (35) and with the findings in Equations (22), (23), (24), we get the solution components

ψ0(xηη,yγγ)=1yγγexηη,
ψ1(xηη,yγγ)=(Lxη)1(Syγ)1[ω1+ωυ3LxηSyγ[yγγexηη(yγγexηη+1)+A0]]=0,A0=ψ0ψ0x,
ψ2(xηη,yγγ)=(Lxη)1(Syγ)1[ω1+ωυ3LxηSyγ[A1]]=0,A1=ψ1ψ0x+ψ0ψ1x.

Thus, we get the solution to the (31) in the form:

ψ(xηη,yγγ)=1yγγexηη. (36)

Note that putting η=γ=1; then the exact solution is,

ψ(x,y)=1yex.

In the following figures, we sketch the 3D plot of the accurate solution of Example 4.2 in Fig. 2(a) which is the same approximate obtained solution, when putting η=γ=1. In Fig. 2(b), we sketch the approximate solution with different values of the fractional orders η and γ: η=γ=1,0.9,0.8.

In Table 2 below, we introduce the absolute exact errors obtained from computing the absolute difference of the accurate and CDLSMD solutions obtained in this application with different values of the variables y=0.1,0.2,0.3 at x=1.

Example 4.3

The nonlinear advection equation of conformable partial differential equation:

γψyγ+ψψx=2yγγ+xηη+(yγγ)3+xηη(yγγ)2,0<γ1, (37)

with initial condition:

ψ(xηη,0)=0. (38)

Solution. Operating the CDLST to Equation (37) and the CLT to Equation (38), to get

Ψ(υ,ω)=2ω2υ+ωυ2+ωLxηSyγ[(yγγ)3+xηη(yγγ)2ψψx]. (39)

Taking (Lxη)1(Syγ)1[Ψ(υ,ω)] of (39), we get

ψ(xηη,yγγ)=(yγγ)2+xηηyγγ+(Lxη)1(Syγ)1[ωLxηSyγ[(yγγ)3+xηη(yγγ)2ψψx]]. (40)

Now, applying the modified decomposition method and substitute (20) in (40) and using results in (22), (23), (24), we get the following solution components

ψ0(xηη,yγγ)=(yγγ)2+xηηyγγ,
ψ1(xηη,yγγ)=(Lxη)1(Syγ)1[ωLxηSyγ[(yγγ)3+xηη(yγγ)2A0]]=0,A0=ψ0ψ0x,
ψ2(xηη,yγγ)=(Lxη)1(Syγ)1[ωLxηSyγ[A1]]=0,A1=ψ1ψ0x+ψ0ψ1x.

Following that, we get the solution of Equation (37):

ψ(xηη,yγγ)=(yγγ)2+xηηyγγ. (41)

Putting η=γ=1; one can obtain the solution,

ψ(x,y)=y2+yx.

In the following figures, we sketch the 3D plot of the accurate solution of Equation (37) in Fig. 3 (a) which is the same approximate obtained solution, when putting η=γ=1. Fig. 3 (b), present the graph of the obtained solution with different values of the fractional orders η and γ: η=γ=1,0.9,0.8.

In Table 3 below, we present the absolute exact errors obtained from computing the absolute difference of the exact and CDLSMD solutions obtained in this problem with different values of the variables y=0.1,0.2,0.3 at x=1.

Example 4.4

The nonlinear Klein-Gordon problem of conformable partial differential equation:

2γψy2γ2ψx2+ψ2=2(xηη)22(yγγ)2+(xηη)4(yγγ)4,0<γ1, (42)

with initial conditions:

ψ(xηη,0)=0,ψy(xηη,0)=0, (43)

and boundary conditions:

ψ(0,yγγ)=0,ψx(0,yγγ)=0. (44)

Solution. Applying the CDLST to (42) and the CLT to (43) and the CST to (44), one can get

Ψ(υ,ω)=4ω2υ3+ω21υ2ω2LxηSyγ[(xηη)4(yγγ)4ψ2]. (45)

Taking (Lxη)1(Syγ)1[Ψ(υ,ω)] of (45), we get

ψ(xηη,yγγ)=(xηη)2(yγγ)2+(Lxη)1(Syγ)1[ω21υ2ω2LxηSyγ[(xηη)4(yγγ)4ψ2]]. (46)

Using the modified decomposition method, and substituting (20) in (46) and using the outcomes in (22), (23), (24), we get the components of the solution as

ψ0(xηη,yγγ)=(xηη)2(yγγ)2,
ψ1(xηη,yγγ)=(Lxη)1(Syγ)1[ω21υ2ω2LxηSyγ[(xηη)4(yγγ)4A0]]=0,A0=ψ02,
ψ2(xηη,yγγ)=(Lxη)1(Syγ)1[ω21υ2ω2LxηSyγ[A1]]=0,A1=2ψ0ψ1.

Thus, we get the solution of (42) in the form

ψ(xηη,yγγ)=(xηη)2(yγγ)2, (47)

Putting η=γ=1; then the solution is,

ψ(x,x)=x2y2.

In the figures below, we sketch the 3D plot of the accurate solution of Equation (42) in Fig. 4 (a) which is the same approximate obtained solution, when putting η=γ=1. In Fig. 4 (b), we sketch the approximate solution at various values of the fractional orders η and γ: η=γ=1,0.9,0.8.

In the following table (Table 4), we introduce the absolute exact errors obtained from computing the absolute difference of the exact and CDLSMD solutions obtained in this example with different values of the variables y=0.1,0.2,0.3 at x=1.

Example 4.5

The telegraph equation of nonlinear conformable partial differential equation is given by:

2ηψx2η=2γψy2γ+2γψyγ+ψ2+exηη2yγγe2xηη4yγγ,0<γ,η1, (48)

with initial conditions

ψ(xηη,0)=exηη,ψy(xηη,0)=2exηη, (49)

and boundary conditions

ψ(0,yγγ)=ψx(0,yγγ)=e2yγγ. (50)

Solution. Applying the CDLST on (48) and the CLT to (49) and the CST to (50), to get

Ψ(υ,ω)=1(υ1)(1+2ω)+ω2ω2υ22ω1LxηSyγ[ψ2e2xηη4yγγ]. (51)

Taking (Lxη)1(Syγ)1[Ψ(υ,ω)] of (51), we get

ψ(xηη,yγγ)=exηη2yγγ+(Lxη)1(Syγ)1[ω2ω2υ22ω1LxηSyγ[ψ2e2xηη4yγγ]]. (52)

Using the modified decomposition method and substituting (20) in (52) and using the findings in (22), (23), (24), we get the components of the solution as

ψ0(xηη,yγγ)=exηη2yγγ,
ψ1(xηη,yγγ)=(Lxη)1(Syγ)1[ω2ω2υ22ω1LxηSyγ[A0e2xηη4yγγ]]=0,A0=ψ02,
ψ2(xηη,yγγ)=(Lxη)1(Syγ)1[ω2ω2υ22ω1LxηSyγ[A1]]=0,A1=2ψ0ψ1.

Following that, we get have the solution of (48) in the form

ψ(xηη,yγγ)=exηη2yγγ, (53)

we can see if η=γ=1; then the accurate solution is,

ψ(x,y)=ex2y.

In the figures below, we sketch the 3D plot of the accurate solution of Equation (48) in Fig. 5 (a) which is the same approximate obtained solution, when putting η=γ=1. In Fig. 5 (b), we sketch the approximate solution with various values of η and γ: η=γ=1,0.9,0.8.

Table 5 below, presents the absolute exact errors obtained from computing the absolute difference of the accurate and CDLSMD solutions obtained in this problem with different values of the variables y=0.1,0.2,0.3 at x=1.

Fig. 1.

Fig. 1

(a) The 3D plots of the solution of Equation (30) gained by the presented method comparing to the exact solution, (b) The CDLSMD solution of ψ(xηη,yγγ) for Equation (30) at η=γ=1,0.9,0.8.

Table 1.

The absolute error of ψ(xηη,yγγ) given by the CDLSMD technique for example 4.1 at various values of η, γ and y.

x y η γ Exact CDLSMD |ψExactψCDLSMD|
1 0.1 0.8 0.8 0.761394 0.778431 1.7037×102
0.2 0.688938 0.672136 1.68025×102
0.3 0.623377 0.588923 3.44542×102
1 0.1 0.9 0.9 0.761394 0.779205 1.78107×102
0.2 0.688938 0.690302 1.36333×103
0.3 0.623377 0.615339 8.03807×103

Fig. 2.

Fig. 2

(a) The 3D plots solution of Equation (36) gained using the presented method comparing to the exact solution (b) The CDLSMD solution of ψ(xηη,yγγ) for Equation (36) at η=γ=1,0.9,0.8.

Table 2.

The absolute error of ψ(xηη,yγγ) gained by the CDLSMD technique for Equation (31) at different values of η, γ and y.

x y η γ Exact CDLSMD |ψExactψCDLSMD|
1 0.1 0.8 0.8 0.728172 0.308522 4.19649×101
0.2 0.456344 0.203932 2.52411×101
0.3 0.184515 0.665233 8.49749×101
1 0.1 0.9 0.9 0.728172 0.57508 1.53092×101
0.2 0.456344 0.207072 2.49272×101
0.3 0.184515 0.14213 3.26647×101

Fig. 3.

Fig. 3

(a) The 3D plots of the solution graph of Equation (41) gained by the presented technique comparing with accurate solution (b) The CLSMD solution of ψ(xηη,yγγ) for Equation (41) at η=γ=1,0.9,0.8.

Table 3.

The absolute error of ψ(xηη,yγγ) obtained by CDLSMD method for Equation (37) at various values of η, γ and y.

x y η γ Exact CDLSMD |ψExactψCDLSMD|
1 0.1 0.8 0.8 0.11 0.286888 1.76888×101
0.2 0.24 0.55014 3.10144×101
0.3 0.39 0.823994 4.33994×101
1 0.1 0.9 0.9 0.11 0.174989 2.15011×101
0.2 0.24 0.358164 1.18164×101
0.3 0.39 0.55912 1.6912×101

Fig. 4.

Fig. 4

(a) The 3D solution graphs of Equation (47) obtained by the presented method comparison with exact solution (b) The CDLSMD solution of ψ(xηη,yγγ) for Equation (47) at η=γ=1,0.9,0.8.

Table 4.

The absolute error of ψ(xηη,yγγ) gained by CDLSMD method for Equation (42) at different values of η, γ and y.

x y η γ Exact CDLSMD |ψExactψCDLSMD|
1 0.1 0.8 0.8 0.01 0.0613254 5.13254×102
0.2 0.04 0.185904 1.45904×101
0.3 0.09 0.355659 2.65659×101
1 0.1 0.9 0.9 0.01 0.0241563 1.41563×102
0.2 0.04 0.084117 4.4117×102
0.3 0.09 0.174521 8.45212×102

Fig. 5.

Fig. 5

(a) The 3D plots of the solution of Equation (53) gained by the presented method comparing to the exact solution (b) The CDLSMD solution of ψ(xηη,yγγ) for Equation (53) at η=γ=1,0.9,0.8.

Table 5.

The error of ψ(xηη,yγγ)g ained by CDLSMD method for Equation (53) at various values of η, γ and y.

x y η γ Exact CDLSMD |ψExactψCDLSMD|
1 0.1 0.8 0.8 2.22554 2.3485 1.22959×101
0.2 1.82212 1.75091 7.12096×102
0.3 1.491823 1.34421 1.47616×101
1 0.1 0.9 0.9 2.22554 2.29642 7.08757×102
0.2 1.82212 1.80229 1.98285×102
0.3 1.491823 1.43211 5.97162×102

6. Results and discussion

This section compares the exact and approximate solutions utilizing tables and graphs to discuss the precision and applicability of the suggested strategy. The 3D plot solutions for Examples 1–5 generated using the current method are shown in (a) in Fig. 1, Fig. 2, Fig. 3, Fig. 4, Fig. 5 in contrast to the precise solutions at η=γ=1. These numbers demonstrate how nearly identical the exact solutions are to the approximations obtained by CDLSMD method. Comparing the line plots of the approximate solutions from the suggested method and the exact solutions of the considered applications (1–5) for a variety values of η and γ, is shown in (b) in Fig. 1, Fig. 2, Fig. 3, Fig. 4, Fig. 5. The figures show that the numerical solutions approach the exact solutions when η,γ1. Table 1, Table 2, Table 3, Table 4, Table 5 present a comparison of each example's exact and approximate solutions in terms of absolute error at x=1 , and at η=γ=0.8 and 0.9 for various values of y. As presented in the tables and figures, it is shown that the proposed method for finding the s converges swiftly towards the accurate solutions.

7. Conclusion

In this article, the CDLST definition has been presented. We started by using the CDLST for a few common tasks. The discussion of a few fundamental theorems and elementary properties connected to the CDLST follows. In order to demonstrate the effectiveness and usefulness of the mentioned double transform, we also used the CDLST combined with the decomposition modified approach to obtain accurate solutions of a number of classes of nonlinear differential equations in the sense of conformable derivatives. We draw the results and compare them to the accurate solutions in the integer case to demonstrate how effectively the results were attained. We conclude that the proposed approach is reliable, suitable, and efficient for obtaining precise solutions to nonlinear conformable problems. Additionally, the computations of the CDLSMD method take less time and effort and require fewer resources than those of other approaches. Thus, our goal in this study is achieved and we proved that the proposed method is applicable and accurate in handling nonlinear conformable fractional problems, and it could present exact solutions unlike other numerical methods. For possible future works, the authors will try solving nonlinear fractional integral equations.

Funding

This research received no external funding.

Author contribution statement

Shams A. Ahmed; Rania Saadeh; Ahmad Qazza; Tarig M. Elzaki: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Data availability statement

No data was used for the research described in the article.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors would like to thank the editor and the kind referees, who choose to remain anonymous, for their insightful comments that helped to improve the paper's final edition.

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