Research article Special Issues

A novel method to study time fractional coupled systems of shallow water equations arising in ocean engineering

  • This study investigates solutions for the time-fractional coupled system of the shallow-water equations. The shallow-water equations are employed for the purpose of elucidating the dynamics of water motion in oceanic or sea environments. Also, the aforementioned system characterizes a thin fluid layer that maintains a hydrostatic equilibrium while exhibiting uniform density. Shallow water flows have a vertical dimension that is considerably smaller in magnitude than the typical horizontal dimension. In the current work, we employ an innovative and effective technique, known as the natural transform decomposition method, to obtain the solutions for these fractional systems. The present methodology entails the utilization of both singular and non-singular kernels for the purpose of handling fractional derivatives. The Banach fixed point theorem is employed to demonstrate the uniqueness and convergence of the obtained solution. The outcomes obtained from the application of the suggested methodology are compared to the exact solution and the results of other numerical methods found in the literature, including the modified homotopy analysis transform method, the residual power series method and the new iterative method. The results obtained from the proposed methodology are presented through the use of tabular and graphical simulations. The current framework effectively captures the behavior exhibited by different fractional orders. The findings illustrate the efficacy of the proposed method.

    Citation: K. Pavani, K. Raghavendar. A novel method to study time fractional coupled systems of shallow water equations arising in ocean engineering[J]. AIMS Mathematics, 2024, 9(1): 542-564. doi: 10.3934/math.2024029

    Related Papers:

    [1] M. Mossa Al-Sawalha, Rasool Shah, Adnan Khan, Osama Y. Ababneh, Thongchai Botmart . Fractional view analysis of Kersten-Krasil'shchik coupled KdV-mKdV systems with non-singular kernel derivatives. AIMS Mathematics, 2022, 7(10): 18334-18359. doi: 10.3934/math.20221010
    [2] Thongchai Botmart, Ravi P. Agarwal, Muhammed Naeem, Adnan Khan, Rasool Shah . On the solution of fractional modified Boussinesq and approximate long wave equations with non-singular kernel operators. AIMS Mathematics, 2022, 7(7): 12483-12513. doi: 10.3934/math.2022693
    [3] Eman A. A. Ziada, Salwa El-Morsy, Osama Moaaz, Sameh S. Askar, Ahmad M. Alshamrani, Monica Botros . Solution of the SIR epidemic model of arbitrary orders containing Caputo-Fabrizio, Atangana-Baleanu and Caputo derivatives. AIMS Mathematics, 2024, 9(7): 18324-18355. doi: 10.3934/math.2024894
    [4] Ahu Ercan . Comparative analysis for fractional nonlinear Sturm-Liouville equations with singular and non-singular kernels. AIMS Mathematics, 2022, 7(7): 13325-13343. doi: 10.3934/math.2022736
    [5] Rahat Zarin, Abdur Raouf, Amir Khan, Aeshah A. Raezah, Usa Wannasingha Humphries . Computational modeling of financial crime population dynamics under different fractional operators. AIMS Mathematics, 2023, 8(9): 20755-20789. doi: 10.3934/math.20231058
    [6] E. Bonyah, C. W. Chukwu, M. L. Juga, Fatmawati . Modeling fractional-order dynamics of Syphilis via Mittag-Leffler law. AIMS Mathematics, 2021, 6(8): 8367-8389. doi: 10.3934/math.2021485
    [7] Mohammed A. Almalahi, Satish K. Panchal, Fahd Jarad, Mohammed S. Abdo, Kamal Shah, Thabet Abdeljawad . Qualitative analysis of a fuzzy Volterra-Fredholm integrodifferential equation with an Atangana-Baleanu fractional derivative. AIMS Mathematics, 2022, 7(9): 15994-16016. doi: 10.3934/math.2022876
    [8] Gulalai, Shabir Ahmad, Fathalla Ali Rihan, Aman Ullah, Qasem M. Al-Mdallal, Ali Akgül . Nonlinear analysis of a nonlinear modified KdV equation under Atangana Baleanu Caputo derivative. AIMS Mathematics, 2022, 7(5): 7847-7865. doi: 10.3934/math.2022439
    [9] Kishor D. Kucche, Sagar T. Sutar, Kottakkaran Sooppy Nisar . Analysis of nonlinear implicit fractional differential equations with the Atangana-Baleanu derivative via measure of non-compactness. AIMS Mathematics, 2024, 9(10): 27058-27079. doi: 10.3934/math.20241316
    [10] M. Mossa Al-Sawalha, Osama Y. Ababneh, Rasool Shah, Amjad khan, Kamsing Nonlaopon . Numerical analysis of fractional-order Whitham-Broer-Kaup equations with non-singular kernel operators. AIMS Mathematics, 2023, 8(1): 2308-2336. doi: 10.3934/math.2023120
  • This study investigates solutions for the time-fractional coupled system of the shallow-water equations. The shallow-water equations are employed for the purpose of elucidating the dynamics of water motion in oceanic or sea environments. Also, the aforementioned system characterizes a thin fluid layer that maintains a hydrostatic equilibrium while exhibiting uniform density. Shallow water flows have a vertical dimension that is considerably smaller in magnitude than the typical horizontal dimension. In the current work, we employ an innovative and effective technique, known as the natural transform decomposition method, to obtain the solutions for these fractional systems. The present methodology entails the utilization of both singular and non-singular kernels for the purpose of handling fractional derivatives. The Banach fixed point theorem is employed to demonstrate the uniqueness and convergence of the obtained solution. The outcomes obtained from the application of the suggested methodology are compared to the exact solution and the results of other numerical methods found in the literature, including the modified homotopy analysis transform method, the residual power series method and the new iterative method. The results obtained from the proposed methodology are presented through the use of tabular and graphical simulations. The current framework effectively captures the behavior exhibited by different fractional orders. The findings illustrate the efficacy of the proposed method.



    Fractional calculus (FC) has been increasingly garnering the interest of many mathematicians and physicians specialties in recent decades. Numerous applications of FC can be found in engineering [1], natural science [2] and many other areas. The fractional differential equations have also been effectively used to model a variety of biological issues, such as hepatitis B [3], methanol detoxification in the body [4] and the human liver [5], as well as other differential physics and thermodynamic models like the dynamical systems [6] and diffusion-wave system [7]. For further details, we will suggest some of the books on FC and its applications, as written by Podlubny [8], Samko et al. [9] and Kilbas et al. [10]. There have been various fractional derivative definitions demonstrated over the past few years. There are numerous benefits and significant implications associated with the utilization of fractional order mathematical modelling. Fractional derivatives describe a key aspect of paradigm generalization and memory consequences. Second, fractional order modelling accurately calculates details between any two points. The integer order models only cover the integer case, but fractional orders can be used at any stage. Compared to integer-order models, fractional-order models better describe memory and hereditary properties of phenomena. The Riemann-Liouville (R-L), Atangana-Baleanu-Caputo (ABC), Caputo (C), Caputo-Fabrizio (CF), Grunwald-Letnikov and Riesz derivatives are the most well-known fractional derivative definitions. The R-L and C fractional derivatives are singular kernels. The index law and other classical requirements were met by this class of fractional differential operators. This singularity prevents full physical structure memory description. Due to this constraint, Caputo and Fabrizio proposed a fractional order centered on the exponential kernel, which has a non-singular kernel [9,11]. Atangana Baleanu developed a non-localized derivative by using the Mittag-Leffler kernel. The CF and ABC derivative offers an alternative approach for describing FC, and it has applications in various fields. It can be used to model systems with memory and hereditary properties, and it provides a way to analyze and describe complex behaviors that cannot be fully captured by integer-order derivatives.

    Researchers have started to develop various innovative ways of approximating the solution of nonlinear differential equations (NDEs) due to the difficulty of obtaining a solution to NDEs. They could be iterative approaches, perturbation methods or numerical methods. Recent years have seen several researchers working on this issue with a focus on studying fractional nonlinear partial differential equation (PDE) solutions by using a variety of techniques, including the reduced differential transform method [12], variational iteration method [13], finite difference method [14], iterative Laplace transform method [15,16] homotopy perturbation method [17], q-homotopy analysis transform method [18], finite element method [11], residual power series transform method [19], the extended sinh-Gordon equation expansion method [20], auxiliary equation mapping method [21], homotopy analysis Sumudu transform method [22], (GG)-expansion method [23], two-variable (GG,1G)-expansion method [24], extended direct algebraic method [25], Hirota bilinear technique [26], modified Kudryashov method [27], symmetry group analysis [28,29] and so on.

    The emergence of shallow-water equations (SWEs), which hold significant importance in the fields of applied mathematics and physics, can be traced back to the latter part of the 18th century. Shallow-water waves can be characterized as the observable displacements of water bodies such as the sea or ocean when subjected to physical examination. Simultaneously, numerous physical phenomena exhibiting similarities to the movements of shallow water waves are observed within the realm of various scientific disciplines, including nuclear physics, plasma physics, fluid dynamics and other related fields. Hence, the investigation of nonlinear PDEs or systems has garnered the interest of applied mathematicians in the modeling of this particular physical phenomenon. The most well-known models for shallow-water waves, according to scientific research, are based on the Klein-Gordon equation, Korteweg-de Vries equation, Benjamin-Bona-Mahony equation, Boussinesq equation, Kadomtsev-Petviashvili equation and shallow-water wave systems. The fluid must be homogeneous and incompressible, the flow must be continuous and the pressure distribution must be hydrostatic for shallow-water flows to exist. The vertical dimension must also be considerably less than the ordinary horizontal dimension. Variations of the SWEs are used to mimic a variety of geophysical flows. We consider one types of the SWEs, namely, the Benney equations [30], which are obtained by considering the two-dimensional and time-dependent movement of an inviscid homogeneous fluid in the presence of a gravitational field. These equations assume that the depth of the fluid is significantly smaller than the horizontal wavelengths under consideration. The equations can be expressed as follows:

    U(ζ,ξ,τ)τ+U(ζ,ξ,τ)U(ζ,ξ,τ)τU(ζ,ξ,τ)ξξ0U(ζ,t,τ)ξdt+W(ζ,τ)ζ=0,W(ζ,τ)τ+ζW0U(ζ,t,τ)ξdt=0, (1.1)

    where ξ represents the stiff bottom and U(ζ,ξ,τ) and W(ζ,τ) denote the horizontal velocity component and the free surface respectively. In this context, the rigid bottom is represented by the equation ξ=0, while the free surface is denoted by ξ=W(ζ,τ). In this scenario, when the horizontal velocity component U remains unaffected by changes in height W, Eq (1.1) simplifies to the system found in classical water theory, specifically in the context of irrotational motion. The wave motion that corresponds to this phenomenon is governed by the time-fractional coupled system of SWEs (TFCSSWE). It represents the analogous wave motion and describes a thin fluid layer in the hydrostatic equilibrium with a constant density. We consider the TFCSSWE [31] to be of the form

    DμτU=WUζUWζ,DμτW=WWζUζ, (1.2)

    with the initial conditions

    U(ζ,0)=19(ζ22ζ+1),W(ζ,0)=2(1ζ)3. (1.3)

    The equations under consideration in this context serve as physical models for a variety of phenomena [32], including tidal events, tsunamis and the hydrodynamics of lakes. Several scholars have recently explored the TFCSSWE by using various techniques, such as modified homotopy analysis transform method (MHATM), and the residual power series method (RPSM) [31], the homotopy perturbation method [33] and new iterative method (NIM) [34].

    To the best of the authors' knowledge, this study represents the first endeavor to investigate the solutions of the TFCSSWE by utilizing the natural transform decomposition method (NTDM) while incorporating the fractional derivatives with in both singular and non-singular kernels. For a class of nonlinear PDEs, Rawashdeh and Maitama [35] proposed the NTDM. The Adomian decomposition method and the natural transform (NT) were two efficient techniques employed in the development of the NTDM. The proposed method handles fractional nonlinear equations without the requirement of a Lagrange multiplier, as is the case with the variational iteration method and Adomian polynomials, as well as with the Adomian decomposition method. The method under consideration does not necessitate any preconceived assumptions, linearization, perturbation or discretization, thereby mitigating the occurrence of rounding errors. As a result, the technique is ready to be applied to a wide range of nonlinear time-fractional PDEs. It is believed that this novel approach can be used to quickly and easily solve a certain class of coupled nonlinear PDEs. To acquire more insight into the impact of fractional-order derivatives, the findings were analyzed from the perspective of an infinite series. Recently, a variety of physical problems, including fractional-order concerns like the Zakharov-Kuznetsov equation [36], Klein-Gordon equation [37], coupled Kawahara and modified Kawahara equations [38] and Swift-Hohenberg equation [39], have been studied by using the proposed method.

    The article's main content is presented in the following order; The primary definitions and some additional findings that are helpful in the investigation of fractional differential equations are included in Section 2. We outline the fundamental methodology for the NTDM in Section 3. The uniqueness and convergence of the solutions are examined in Section 4. The suggested strategy is put into practice in Section 5 to determine the precise solution to the TFCSSWE. The numerical results and discussion are presented in Section 6. Finally, we give our conclusions in Section 7.

    In this section, we give some of the well-known fractional derivative definitions mentioned below.

    Definition 2.1. [40] The C derivative of fractional order μ of function U(τ)Cqν for ν1 is defined as

    DμτU(τ)={dqU(τ)dτq,μ=qN,1Γ(qμ)τ0(τζ)qμ1Uq(ζ)dζ,q1<μ<q,qN. (2.1)

    Definition 2.2. [41] The CF fractional derivative of the function U(τ)H1(0,T) is defined by

    CFDμτU(τ)=11μτ0U(ζ)exp(μ(τζ)1μ)dζ,τ0,0<μ1. (2.2)

    Definition 2.3. [42] The ABC derivative of fractional order μ of function U(τ)H1(0,T) is defined as

    ABCDμτU(τ)=M[μ]1μτ0U(ζ)Eμ(μ(τζ)μ1μ)dζ,0<μ1. (2.3)

    Definition 2.4. [43] The definition of the NT is given as

    N+[U(τ)]=0esτU(vτ)dτ,v,s>0. (2.4)

    Definition 2.5. [44] The definition of the NT of the C derivative is given as

    N+[C0DμτU(τ)]=(sv)μ(N+[U(τ)]1sU(0)). (2.5)

    Definition 2.6. [45] The definition of the NT of the CF derivative is given as

    N+[CF0DμτU(τ)]=1φ(μ,v,s)(N+[U(τ)]1sU(0)), (2.6)

    where φ(μ,v,s)=1μ+μ(vs).

    Definition 2.7. [46] The definition of the NT of the ABC derivative is given by

    N+[ABC0DμτU(τ)]=1ψ(μ,v,s)(N+[U(τ)]1sU(0)), (2.7)

    where ψ(μ,v,s)=1μ+μ(vs)μM[μ].

    In this section, the NTDM is applied to solve the TFCSSWE by considering the three aforementioned fractional derivatives.

    NTDMC: By taking the NT of Eq (1.2) in the C sense, with the initial condition given by Eq (1.3), we obtain

    (sv)μ[N+(U(ζ,τ))19(ζ22ζ+1)s]=N+[WUζUWζ],(sv)μ[N+(W(ζ,τ))2(1ζ)3s]=N+[UζWWζ]. (3.1)

    From Eq (3.1), we can apply the inverse NT on both sides:

    U(ζ,τ)=N1[19(ζ22ζ+1)s+(vs)μN+[WUζUWζ]],W(ζ,τ)=N1[2(1ζ)3s+(vs)μN+[UζWWζ]]. (3.2)

    The nonlinear terms can be represented as

    WUζ=k=0Ak,UWζ=k=0Bk,WWζ=k=0Ck, (3.3)

    where Ak, Bk and Ck are the Adomian polynomials.

    U(ζ,τ) and W(ζ,τ) are the unknown functions, which have infinite series of the following respective forms:

    U(ζ,τ)=k=0Uk(ζ,τ),W(ζ,τ)=k=0Wk(ζ,τ). (3.4)

    Making substitutions of Eqs (3.3) and (3.4) into Eq (3.2), we obtain

    k=0Uk(ζ,τ)=N1[19(ζ22ζ+1)s]+N1[(vs)μN+[k=0kj=0Wj(Ukj)ζ+k=0kj=0Uj(Wkj)ζ]],k=0Wk(ζ,τ)=N1[2(1ζ)3s]+N1[(vs)μN+[k=0(Uk)ζ+k=0kj=0Wj(Wkj)ζ]]. (3.5)

    From Eq (3.5), we have

    CU0(ζ,τ)=N1[19(ζ22ζ+1)s],CW0(ζ,τ)=N1[2(1ζ)3s],CU1(ζ,τ)=N1[(vs)μN+[U0ζW0+U0W0ζ]],CW1(ζ,τ)=N1[(vs)μN+[(U0)ζ+W0W0ζ]],CU2(ζ,τ)=N1[(vs)μN+[U1ζW0+U0ζW1+U1W0ζ+U0W1ζ]],CW2(ζ,τ)=N1[(vs)μN+[(U1)ζ+W1W0ζ+W0W1ζ]],CUk+1(ζ,τ)=N1[(vs)μN+[kj=0Wj(Ukj)ζ+kj=0Uj(Wkj)ζ],k0,CWk+1(ζ,τ)=N1[(vs)μN+[(Uk)ζ+kj=0Wj(Wkj)ζ]],k0. (3.6)

    Making substitutions of Eq (3.6) into Eq (3.4), we obtain the series solution as

    CU(ζ,τ)=CU0(ζ,τ)+CU1(ζ,τ)+CU2(ζ,τ)+,CW(ζ,τ)=CW0(ζ,τ)+CW1(ζ,τ)+CW2(ζ,τ)+. (3.7)

    NTDMCF: By taking the NT of Eq (1.2) in the CF sense, with the initial condition given by Eq (1.3), we obtain

    1φ(μ,v,s)(N+[U(ζ,τ)]19(ζ22ζ+1)s)=N+[WUζUWζ],1φ(μ,v,s)(N+[W(ζ,τ)]2(1ζ)3s)=N+[UζWWζ]. (3.8)

    From Eq (3.8), we can apply the inverse NT on both sides:

    U(ζ,τ)=N1[19(ζ22ζ+1)s+φ(μ,v,s)N+[WUζUWζ]],W(ζ,τ)=N1[2(1ζ)3s+φ(μ,v,s)N+[UζWWζ]]. (3.9)

    Now, making substitutions of Eqs (3.3) and (3.4) into Eq (3.9), we have

    k=0Uk(ζ,τ)=N1[19(ζ22ζ+1)s]+N1[φ(μ,v,s)N+[k=0kj=0Wj(Ukj)ζ+k=0kj=0Uj(Wkj)ζ]],k=0Wk(ζ,τ)=N1[2(1ζ)3s]+N1[φ(μ,v,s)N+[k=0(Uk)ζ+k=0kj=0Wj(Wkj)ζ]]. (3.10)

    From Eq (3.10), we have

    CFU0(ζ,τ)=N1[19(ζ22ζ+1)s],CFW0(ζ,τ)=N1[2(1ζ)3s],CFU1(ζ,τ)=N1[φ(μ,v,s)N+[U0ζW0+U0W0ζ]],CFW1(ζ,τ)=N1[φ(μ,v,s)N+[(U0)ζ+W0W0ζ]],CFU2(ζ,τ)=N1[φ(μ,v,s)N+[U1ζW0+U0ζW1+U1W0ζ+U0W1ζ]],CFW2(ζ,τ)=N1[φ(μ,v,s)N+[(U1)ζ+W1W0ζ+W0W1ζ]],CFUk+1(ζ,τ)=N1[φ(μ,v,s)N+[kj=0Wj(Ukj)ζ+kj=0Uj(Wkj)ζ]],k0,CFWk+1(ζ,τ)=N1[φ(μ,v,s)N+[(Uk)ζ+kj=0Wj(Wkj)ζ]],k0. (3.11)

    By substituting Eq (3.11) into Eq (3.4), we obtain the series solution as

    CFU(ζ,τ)=CFU0(ζ,τ)+CFU1(ζ,τ)+CFU2(ζ,τ)+,CFW(ζ,τ)=CFW0(ζ,τ)+CFW1(ζ,τ)+CFW2(ζ,τ)+. (3.12)

    NTDMABC: By taking the NT of Eq (1.2), using the ABC derivative along with the initial condition given by Eq (1.3), we obtain

    1ψ(μ,v,s)(N+[U(ζ,τ)]19(ζ22ζ+1)s)=N+[WUζUWζ],1ψ(μ,v,s)(N+[W(ζ,τ)]2(1ζ)3s)=N+[UζWWζ]. (3.13)

    From Eq (3.13), we can apply the inverse NT on both sides:

    U(ζ,τ)=N1[19(ζ22ζ+1)s+ψ(μ,v,s)N+[WUζUWζ]],W(ζ,τ)=N1[2(1ζ)3s+ψ(μ,v,s)N+[UζWWζ]]. (3.14)

    Now, making substitutions of Eqs (3.3) and (3.4) into Eq (3.14), we have

    k=0Uk(ζ,τ)=N1[(ζ1)29s]+N1[ψ(μ,v,s)N+[k=0kj=0Wj(Ukj)ζ+k=0kj=0Uj(Wkj)ζ]],k=0Wk(ζ,τ)=N1[2(1ζ)3s]+N1[ψ(μ,v,s)N+[k=0(Uk)ζ+k=0kj=0Wj(Wkj)ζ]]. (3.15)

    From Eq (3.15), we obtain

    ABCU0(ζ,τ)=N1[19(ζ22ζ+1)s],ABCW0(ζ,τ)=N1[2(1ζ)3s],ABCU1(ζ,τ)=N1[ψ(μ,v,s)N+[U0ζW0+U0W0ζ]],ABCW1(ζ,τ)=N1[ψ(μ,v,s)N+[(U0)ζ+W0W0ζ]],ABCU2(ζ,τ)=N1[ψ(μ,v,s)N+[U1ζW0+U0ζW1+U1W0ζ+U0W1ζ]],ABCW2(ζ,τ)=N1[ψ(μ,v,s)N+[(U1)ζ+W1W0ζ+W0W1ζ]],ABCUk+1(ζ,τ)=N1[ψ(μ,v,s)N+[kj=0Wj(Ukj)ζ+kj=0Uj(Wkj)ζ]],k0,ABCWk+1(ζ,τ)=N1[ψ(μ,v,s)N+[(Uk)ζ+kj=0Wj(Wkj)ζ]],k0. (3.16)

    By substituting Eq (3.16) into Eq (3.4), we obtain the series solution as

    ABCU(ζ,τ)=ABCU0(ζ,τ)+ABCU1(ζ,τ)+ABCU2(ζ,τ)+,ABCW(ζ,τ)=ABCW0(ζ,τ)+ABCW1(ζ,τ)+ABCW2(ζ,τ)+. (3.17)

    The subsequent analysis will establish that the given set of sufficient conditions guarantees the existence of a unique solution. Furthermore, convergence analysis is also presented. The existence of solutions in the case of the NTDM and convergence of the solutions is established for three derivatives [44].

    Theorem 4.1. For 0<(δ1+δ2)τμΓ(1+μ)<1 and 0<(δ3+δ4)τμΓ(1+μ)<1, the NTDMC solution is unique.

    Proof. Let H=(C[J],.) be the Banach space with ϕ(τ)=maxτJϕ(τ) continuous functions on J. Let L:HH be a nonlinear mapping, where

    UCk+1(ζ,τ)=UC0+N1[(vs)μN+[R1(Uk(ζ,τ))]]+N1[(vs)μN+[F1(Uk(ζ,τ))]],k0,WCk+1(ζ,τ)=WC0+N1[(vs)μN+[R2(Wk(ζ,τ))]]+N1[(vs)μN+[F2(Wk(ζ,τ))]],k0.

    Let us suppose that R1(U)R1(U)∣<δ1UU, F1(U)F1(U)∣<δ2UU and R2(W)R2(W)∣<δ3WW, F2(W)F2(W)∣<δ4WW, where δ1, δ2 and δ3, δ4 are Lipschitz constants and U:=U(ζ,τ), U:=U(ζ,τ), W:=W(ζ,τ) and W:=W(ζ,τ) are four different function values. Here, F1 represents WUζ+UWζ, R2 denotes Uζ and F2 denotes WWζ.

    L1(U)L1(U)=maxτJ|N1[(vs)μN+[R1(U)+F1(U)]]N1[(vs)μN+[R1(U)+F1(U)]]|maxτJ|N1[(vs)μN+[R1(U)R1(U)]+(vs)μN+[F1(U)F1(U)]]|maxτJ[δ1N1[(vs)μN+|UU|]+δ2N1[(vs)μN+|UU|]]maxτJ(δ1+δ2)[N1(vs)μ[N+|UU|]](δ1+δ2)[N1[(vs)μN+UU]]=(δ1+δ2)τμΓ(μ+1)UU.

    Similarly, L2(W)L2(W)=(δ3+δ4)τμΓ(μ+1)WW.

    L is a contraction, as 0<(δ1+δ2)τμΓ(1+μ)<1 and 0<(δ3+δ4)τμΓ(1+μ)<1. From the perspective of the Banach fixed-point theorem, the solution is unique.

    Using procedure similar to Theorem 4.1, we state the following.

    Theorem 4.2. The NTDMCF solution is unique when 0<(δ1+δ2)(1μ+μτ)<1 and 0<(δ3+δ4)(1μ+μτ)<1.

    Theorem 4.3. The NTDMABC solution is unique when 0<(δ1+δ2)(1μ+μτμΓ(μ+1))<1 and 0<(δ3+δ4)(1μ+μτμΓ(μ+1))<1.

    Theorem 4.4. The NTDMC solution is convergent.

    Proof. Let Um=mk=0Uk(ζ,τ) and Wm=mk=0Wk(ζ,τ). To prove that Um and Wm are Cauchy sequences in H, consider the following:

    UmUn=maxτJ|UmUn|=maxτJ|mr=n+1Ur|,n=1,2,3,,maxτJ|N1[(vs)μN+[mr=n+1(R1(Ur1)+F1(Ur1))]]|=maxτJ|N1[(vs)μN+[m1r=nR1(Ur)+F1(Ur)]]|maxτJ|N1[(vs)μN+[R1(Um1)R1(Un1)]]|+maxτJ|N1[(vs)μN+[F1(Um1)F1(Un1)]]|δ1maxτJ|N1(vs)μ[N+[R1(Um1)R1(Un1)]]|+δ2maxτJ|N1(vs)μ[N+[F1(Um1)F1(Un1)]]|=(δ1+δ2)τμΓ(μ+1)Um1Un1.

    Similarly, WmWn=(δ3+δ4)τμΓ(μ+1)Wm1Wn1.

    Let m=n+1 ; then,

    Un+1UnδUnUn1δ2Un1Un2δnU1U0.

    Similarly, Wn+1WnρnW1W0, where δ=(δ1+δ2)τμΓ(μ+1) and ρ=(δ3+δ4)τμΓ(μ+1). Moreover, we have

    UmUnUn+1Un+Un+2Un+1++UmUm1(δn+δn+1++δm1)U1U0δn(1δmn1δ)U1.

    Similarly, WmWnρn(1ρmn1ρ)W1.

    Because 0<δ<1 and 0<ρ<1, we get that 1δmn<1 and 1ρmn<1.

    Therefore, UmUnδn1δmaxτJU1 and WmWnρn1ρmaxτJW1.

    Since U1< and W1< results in n, UmUn0 and WmWn0. As a result, Um and Wm are Cauchy sequences in H; thus, the series Um and Wm are convergent.

    Using a procedure similar to Theorem 4.4, we state the following:

    Theorem 4.5. The NTDMCF solution is convergent.

    Theorem 4.6. The NTDMABC solution is convergent.

    In this section, the approximate solutions of the TFCSSWE , as obtained by applying three fractional derivatives namely, the C, CF and ABC derivatives, are presented.

    Consider the TFCSSWE given by Eq (1.2), along with the initial conditions given by Eq (1.3), and when μ=1, the exact solution [31] is given by

    U(ζ,τ)=(ζ1)29(τ1)2,W(ζ,τ)=2(ζ1)3(τ1). (5.1)

    NTDMC: We get the NTDMC solutions as follows:

    CU0(ζ,τ)=19(ζ22ζ+1),CW0(ζ,τ)=2(1ζ)3,CU1(ζ,τ)=2τμ(1+ζ)29Γ(1+μ),CW1(ζ,τ)=2τμ(1+ζ)3Γ(1+μ),CU2(ζ,τ)=2τ2μ(1+ζ)23Γ(1+2μ),CW2(ζ,τ)=4τ2μ(1+τ)3Γ(1+2μ).

    Similar expressions for CUk(ζ,τ) and CWk(ζ,τ) for k4 can also be obtained by using Eq (3.6). We get the series solution from Eq (3.7) as follows:

    CU(ζ,τ)=19(ζ22ζ+1)+2τμ(1+ζ)29Γ(1+μ)+2τ2μ(1+ζ)23Γ(1+2μ)+,CW(ζ,τ)=2(1ζ)3+2τμ(1+ζ)3Γ(1+μ)+4τ2μ(1+τ)3Γ(1+2μ)+.

    NTDMCF: We get the NTDMCF solutions as follows:

    CFU0(ζ,τ)=19(ζ22ζ+1),CFW0(ζ,τ)=2(1ζ)3,CFU1(ζ,τ)=2(1+ζ)2(1μ+μτ)9,CFW1(ζ,τ)=2(1+ζ)(1μ+μτ)3,CFU2(ζ,τ)=(1+ζ)23[2(1+μ)2+μ2τ24μτ(1+μ)],CFW2(ζ,τ)=2(1+ζ)3[4μτ(1+μ)μ2τ22(1+μ)2].

    Similar expressions for CFUk(ζ,τ) and CFWk(ζ,τ) for k4 can also be obtained by using Eq (3.11). We get the series solution from Eq (3.12) as follows:

    CFU(ζ,τ)=19(ζ22ζ+1)+2(1+ζ)2(1μ+μτ)9+(1+ζ)23[2(1+μ)2+μ2τ24μτ(1+μ)]+,CFW(ζ,τ)=2(1ζ)32(1+ζ)(1μ+μτ)3+2(1+ζ)3[4μτ(1+μ)μ2τ22(1+μ)2]+.

    NTDMABC: We get the NTDMABC solutions as follows:

    ABCU0(ζ,τ)=19(ζ22ζ+1),ABCW0(ζ,τ)=2(1ζ)3,ABCU1(ζ,τ)=2(1+ζ)29[1μ+μτμΓ(1+μ)],ABCW1(ζ,τ)=2(1+ζ)23[1+μμτμΓ(1+μ)],ABCU2(ζ,τ)=2(1+ζ)23[(1μ)2+2μ(1μ)τμΓ(1+μ)+μ2τ2μΓ(1+2μ)],ABCW2(ζ,τ)=4(1+ζ)3[(1μ)2+2μ(1μ)τμΓ(1+μ)+μ2τ2μΓ(1+2μ)].

    Similar expressions for ABCUk(ζ,τ) and ABCWk(ζ,τ) for k4 can also be obtained by using Eq (3.16). We get the series solution from Eq (3.17) as follows:

    ABCU(ζ,τ)=19(ζ22ζ+1)+2(1+ζ)29[1μ+μτμΓ(1+μ)]+2(1+ζ)23[(1μ)2+2μ(1μ)τμΓ(1+μ)+μ2τ2μΓ(1+2μ)]+,ABCW(ζ,τ)=2(1ζ)3+2(1+ζ)23[1+μμτμΓ(1+μ)]4(1+ζ)3[(1μ)2+2μ(1μ)τμΓ(1+μ)+μ2τ2μΓ(1+2μ)]+.

    In this section, we present the numerical and graphical simulations of the TFCSSWE by using the NTDM. The solutions were computed by using distinct spatial and temporal variables for different fractional-order values, as shown in Tables 16. Figures 14 present the results of numerical simulations that exploit the animations of the solutions, showcasing their dynamic behavior. Tables 14 present the absolute error of the TFCSSWE for different values of ζ and τ, with μ set to 1. Tables 1 and 2 present a comparative analysis of the absolute errors associated with the horizontal velocity U(ζ,τ) and free surface W(ζ,τ), as conducted by employing MHATM and RPSM methodologies [31]. Tables 3 and 4 present a comparative analysis of the absolute errors of U and W, as based on the NIM [34].

    Table 1.  Absolute error of U(ζ,τ) with various values of ζ, τ at μ = 1.
    ζ τ NTDMC NTDMCF NTDMABC MHATM [31] RPSM [31]
    0.1 0.1 7.11111E-07 7.11111E-07 7.11111E-07 7.11111E-07 8.27052E-05
    0.2 5.22000E-05 5.22000E-05 5.22000E-05 5.22000E-05 9.40010E-04
    0.3 6.96269E-04 6.96269E-04 6.96269E-04 6.96269E-04 4.66383E-03
    0.2 0.1 5.61866E-07 5.61866E-07 5.61866E-07 5.61866E-07 6.53415E-05
    0.2 4.12444E-05 4.12444E-05 4.12444E-05 4.12444E-05 7.42537E-04
    0.3 5.50139E-04 5.50139E-04 5.50139E-04 5.50139E-04 3.68358E-03
    0.3 0.1 4.30178E-07 4.30178E-07 4.30178E-07 4.30178E-07 5.00213E-05
    0.2 3.15778E-05 3.15778E-05 3.15778E-05 3.15778E-05 5.68320E-04
    0.3 4.21200E-04 4.21200E-04 4.21200E-04 4.21200E-04 2.88188E-03

     | Show Table
    DownLoad: CSV
    Table 2.  Absolute error of W(ζ,τ) with various values of ζ, τ at μ = 1.
    ζ τ NTDMC NTDMCF NTDMABC MHATM [31] RPSM [31]
    0.1 0.1 6.66667E-07 6.66667E-07 6.66667E-07 6.66667E-07 9.15580E-05
    0.2 4.80000E-05 4.80000E-05 4.80000E-05 4.80000E-05 1.02467E-04
    0.3 6.24857E-04 6.24857E-04 6.24857E-04 6.24857E-04 4.95146E-03
    0.2 0.1 5.92593E-07 5.92593E-07 5.92593E-07 5.92593E-07 7.97169E-05
    0.2 4.26667E-05 4.26667E-05 4.26667E-05 4.26667E-05 8.83779E-04
    0.3 5.55429E-04 5.55429E-04 5.55429E-04 5.55429E-04 4.26263E-03
    0.3 0.1 5.18519E-07 5.18519E-07 5.18519E-07 5.18519E-07 6.78757E-05
    0.2 3.73333E-05 3.73333E-05 3.73333E-05 3.73333E-05 7.42887E-04
    0.3 4.86000E-04 4.86000E-04 4.86000E-04 4.86000E-04 3.57380E-03

     | Show Table
    DownLoad: CSV
    Table 3.  Absolute error of U(ζ,τ) with various values of ζ, τ at μ = 1.
    ζ τ NTDMC NTDMCF NTDMABC NIM[34]
    2.5 0.025 1.612837E-05 1.612837E-05 1.612837E-05 1.092004E-05
    0.05 1.333102E-04 1.333102E-04 1.333102E-04 9.164358E-05
    0.075 4.653260E-04 4.653260E-04 4.653260E-04 3.247010E-04
    0.1 1.141975E-03 1.141975E-03 1.141975E-03 8.086420E-04
    5 0.025 1.146906E-04 1.146906E-04 1.146906E-04 7.765359E-05
    0.05 9.479840E-04 9.479840E-04 9.479840E-04 6.516877E-04
    0.075 3.308985E-03 3.308985E-03 3.308985E-03 2.308985E-03
    0.1 8.120713E-03 8.120713E-03 8.120713E-03 5.750343E-03
    7.5 0.025 3.028549E-04 3.028549E-04 3.028549E-04 2.050540E-04
    0.05 2.503270E-03 2.503270E-03 2.503270E-03 1.720863E-03
    0.075 8.737788E-03 8.737788E-03 8.737788E-03 6.097163E-03
    0.1 2.144376E-02 2.144376E-02 2.144376E-02 1.520000E-02
    10 0.025 5.806213E-04 5.806213E-04 5.806213E-04 3.931213E-04
    0.05 4.799169E-03 4.799169E-03 4.799169E-03 3.299169E-03
    0.075 1.675173E-02 1.675173E-02 1.675173E-02 1.168923E-02
    0.1 4.111111E-02 4.111111E-02 4.111111E-02 2.911111E-02

     | Show Table
    DownLoad: CSV
    Table 4.  Absolute error of W(ζ,τ) with different values of ζ, τ at μ = 1.
    ζ τ NTDMC NTDMCF NTDMABC NIM[34]
    2.5 0.025 1.602564E-05 1.602564E-05 1.602564E-05 1.255342E-05
    0.05 1.315789E-04 1.315789E-04 1.315789E-04 1.038012E-04
    0.075 4.560811E-04 4.560811E-04 4.560811E-04 3.623311E-04
    0.1 1.111111E-03 1.111111E-03 1.111111E-03 8.888889E-04
    5 0.025 4.273504E-05 4.273504E-05 4.273504E-05 3.347578E-05
    0.05 3.508772E-04 3.508772E-04 3.508772E-04 2.768031E-04
    0.075 1.216216E-03 1.216216E-03 1.216216E-03 9.662162E-04
    0.1 2.962963E-03 2.962963E-03 2.962963E-03 2.370370E-03
    7.5 0.025 6.944444E-05 6.944444E-05 6.944444E-05 5.439815E-05
    0.05 5.701754E-04 5.701754E-04 5.701754E-04 4.498051E-04
    0.075 1.976351E-03 1.976351E-03 1.976351E-03 1.570101E-03
    0.1 4.814815E-03 4.814815E-03 4.814815E-03 3.851852E-03
    10 0.025 9.615385E-05 9.615385E-05 9.615385E-05 7.532051E-05
    0.05 7.894737E-04 7.894737E-04 7.894737E-04 6.228070E-04
    0.075 2.736486E-03 2.736486E-03 2.736486E-03 2.173986E-03
    0.1 6.666667E-03 6.666667E-03 6.666667E-03 5.333333E-03

     | Show Table
    DownLoad: CSV
    Table 5.  Approximate solution of U(ζ,τ) for various values of μ, τ and ζ.
    ζ τ μ=0.50 μ=0.70
    NTDMC NTDMCF NTDMABC NIM[34] NTDMC NTDMCF NTDMABC NIM[34]
    2.5 0.025 0.376706 0.900117 1.062787 0.380492 0.298507 0.559729 0.619926 0.298803
    0.05 0.451156 0.925468 1.146063 0.461865 0.335802 0.584918 0.676395 0.337071
    0.075 0.517009 0.951054 1.212144 0.536682 0.371904 0.610567 0.726692 0.374877
    0.1 0.578412 0.976875 1.269325 0.608701 0.407868 0.636675 0.773752 0.413306
    5 0.025 2.678800 6.400833 7.557599 2.705720 2.122716 3.980300 4.408366 2.124820
    0.05 3.208225 6.581111 8.149783 3.284370 2.387931 4.159422 4.809920 2.396950
    0.075 3.676513 6.763056 8.619693 3.816410 2.644653 4.341811 5.167588 2.665790
    0.1 4.113150 6.946667 9.026309 4.328540 2.900395 4.527467 5.502241 2.939070
    7.5 0.025 7.073705 16.902201 19.956786 7.144800 5.605298 10.510479 11.640843 5.610850
    0.05 8.471719 17.378247 21.520521 8.672800 6.305630 10.983474 12.701196 6.329450
    0.075 9.708293 17.858694 22.761377 10.077700 6.983537 11.465095 13.645663 7.039350
    0.1 10.861229 18.343542 23.835099 11.430000 7.658856 11.955342 14.529354 7.760970
    10 0.025 13.561423 32.404219 38.260347 13.697700 10.746251 20.150269 22.317355 10.756900
    0.05 16.241639 33.316875 41.258277 16.627100 12.088901 21.057075 24.350221 12.134600
    0.075 18.612349 34.237969 43.637197 19.320600 13.388556 21.980419 26.160916 13.495600
    0.1 20.822847 35.167500 45.695694 21.913200 14.683250 22.920300 27.855093 14.879000
    μ=0.90 μ=1
    2.5 0.025 0.269964 0.333379 0.343012 0.269985 0.262968 0.262968 0.262968 0.262974
    0.05 0.289145 0.352518 0.368803 0.289279 0.276875 0.276875 0.276875 0.276917
    0.075 0.308968 0.372417 0.394591 0.309367 0.291718 0.291718 0.291718 0.291859
    0.1 0.329629 0.393075 0.420732 0.330496 0.307500 0.307500 0.307500 0.307833
    5 0.025 1.919748 2.370700 2.439199 1.919890 1.870000 1.870000 1.870000 1.870040
    0.05 2.056145 2.506800 2.622604 2.057090 1.968889 1.968889 1.968889 1.969190
    0.075 2.197106 2.648300 2.805981 2.199940 2.074444 2.074444 2.074444 2.075440
    0.1 2.344029 2.795200 2.991874 2.350200 2.186667 2.186667 2.186667 2.189040
    7.5 0.025 5.069336 6.260129 6.441009 5.069720 4.937969 4.937969 4.937969 4.938070
    0.05 5.429507 6.619519 6.925315 5.432010 5.199097 5.199097 5.199097 5.199880
    0.075 5.081733 6.993167 7.409545 5.809220 5.477829 5.477829 5.477829 5.480470
    0.1 6.189702 7.381075 7.900416 6.205980 5.774167 5.774167 5.774167 5.780430
    10 0.025 9.718727 12.001669 12.348444 9.719470 9.466875 9.466875 9.466875 9.467060
    0.05 10.409232 12.690675 13.276935 10.414000 9.967500 9.967500 9.967500 9.969000
    0.075 11.122849 13.407019 14.205281 11.137200 10.501875 10.501875 10.501875 10.506900
    0.1 11.866648 14.150700 15.146359 11.897900 11.070000 11.070000 11.070000 11.082000

     | Show Table
    DownLoad: CSV
    Table 6.  Approximate solution of W(ζ,τ) for various values of μ, τ and ζ.
    ζ τ μ=0.50 μ=0.70
    NTDMC NTDMCF NTDMABC NIM[34] NTDMC NTDMCF NTDMABC NIM [34]
    2.5 0.025 -1.228412 -2.037656 -2.280119 -1.230940 -1.092412 -1.518806 -1.612651 -1.092610
    0.05 -1.352313 -2.075625 -2.403469 -1.359450 -1.159461 -1.558225 -1.700067 -1.160310
    0.075 -1.459019 -2.113906 -2.501029 -1.472130 -1.222384 -1.598256 -1.777481 -1.224370
    0.1 -1.556825 -2.152500 -2.585237 -1.577020 -1.283687 -1.638900 -1.849574 -1.287310
    5 0.025 -3.275766 -5.433750 -6.080316 -3.282500 -2.913099 -4.050150 -4.300402 -2.913620
    0.05 -3.606168 -5.535000 -6.409253 -3.625210 -3.091896 -4.155267 -4.533512 -3.094150
    0.075 -3.890718 -5.637083 -6.669411 -3.925690 -3.259692 -4.262017 -4.739949 -3.264980
    0.1 -4.151532 -5.740000 -6.893966 -4.205380 -3.423165 -4.370400 -4.932197 -3.432830
    7.5 0.025 -5.323120 -8.829844 -9.880514 -5.334060 -4.733786 -6.581494 -6.988153 -4.734640
    0.05 -5.860024 -8.994375 -10.415036 -5.890960 -5.024332 -6.752308 -7.366957 -5.028000
    0.075 -6.322417 -9.160260 -10.837793 -6.379250 -5.296999 -6.925777 -7.702419 -5.305590
    0.1 -6.746241 -9.327500 -11.202695 -6.833740 -5.562643 -7.101900 -8.014821 -5.578350
    10 0.025 -7.370474 -12.225938 -13.680712 -7.385620 -6.554472 -9.112838 -9.675904 -6.555660
    0.05 -8.113879 -12.453750 -14.420819 -8.156710 -6.956767 -9.349350 -10.200401 -6.961840
    0.075 -8.754116 -12.683438 -15.006174 -8.832810 -7.334307 -9.589538 -10.664887 -7.346200
    0.1 -9.340949 -12.915000 -15.511423 -9.462100 -7.702121 -9.833400 -11.097444 -7.723870
    μ=0.90 μ=1
    2.5 0.025 -1.039149 -1.152006 -1.168627 -1.039160 -1.025625 -1.025625 -1.025625 -1.025630
    0.05 -1.075576 -1.185025 -1.212782 -1.075660 -1.052500 -1.052500 -1.052500 -1.052530
    0.075 -1.112303 -1.219056 -1.256433 -1.112570 -1.080625 -1.080625 -1.080625 -1.080720
    0.1 -1.149805 -1.254100 -1.300245 -1.150380 -1.110000 -1.110000 -1.110000 -1.110220
    5 0.025 -2.771066 -3.072017 -3.116338 -2.771100 -2.735000 -2.735000 -2.735000 -2.735010
    0.05 -2.868202 -3.160067 -3.234086 -2.868440 -2.806667 -2.806667 -2.806667 -2.806740
    0.075 -2.966143 -3.250817 -3.350488 -2.966850 -2.881667 -2.881667 -2.881667 -2.881920
    0.1 -3.066145 -3.344267 -3.467321 -3.067690 -2.960000 -2.960000 -2.960000 -2.960590
    7.5 0.025 -4.502982 -4.992027 -5.064049 -4.503040 -4.444375 -4.444375 -4.444375 -4.444390
    0.05 -4.660829 -5.135108 -5.255389 -4.661210 -4.560833 -4.560833 -4.560833 -4.560950
    0.075 -4.819982 -5.282577 -5.444543 -4.821130 -4.682708 -4.682708 -4.682708 -4.683110
    0.1 -4.982486 -5.434433 -5.634397 -4.984990 -4.810000 -4.810000 -4.810000 -4.810960
    10 0.025 -6.234898 -6.912038 -7.011761 -6.234980 -6.153750 -6.153750 -6.153750 -6.153770
    0.05 -6.453455 -7.110150 -7.276693 -6.453990 -6.315000 -6.315000 -6.315000 -6.315170
    0.075 -6.673821 -7.314338 -7.538598 -6.675420 -6.483750 -6.483750 -6.483750 -6.484310
    0.1 -6.898827 -7.524600 -7.801473 -6.902300 -6.660000 -6.660000 -6.660000 -6.661330

     | Show Table
    DownLoad: CSV
    Figure 1.  Approximate solution of U(ζ,τ) with τ=0.1 for different values of μ.
    Figure 2.  Approximate solution of W(ζ,τ) with τ=0.1 for different values of μ.
    Figure 3.  Surface plots of U(ζ,τ) for different values of μ.
    Figure 4.  Surface plots of W(ζ,τ) for different values of μ.

    Based on the data presented in Tables 14, it is evident that the suggested method solutions for all three derivatives exhibit high levels of concordance with the approaches that have been reported in the literature. The provided test example showcases the efficacy, adaptability and accuracy of the proposed methodology. This observation illustrates that the proposed numerical method yields more favorable outcomes when applied to NDEs. After successfully validating the strategy for the integer-order model, the authors were motivated to apply the recommended method to solve the comparable model, i.e., a temporal fractional-order model. Table 5 demonstrates that the behavior of the horizontal velocity derived from both singular and non-singular kernel derivatives exhibits a further significant increase when the fractional order decreases. Table 6 illustrates the observed behavior of the free surface as derived from both singular and non-singular kernel derivatives, we can observe substantial decreases as the fractional order decreases.

    In Figures 1 and 2, the graphical representations respectively showcase the estimated solutions U(ζ,τ) and W(ζ,τ) for μ=0.25,0.50,0.75,1, 0ζ5 when τ is set to 0.1. As the value of ζ increases and the fractional order decreases, Figure 1 illustrates that the horizontal velocity component U(ζ,τ) increases under the condition of a constant τ. According to Figure 2, as the value of ζ increases and the fractional order decreases, the free surface W(ζ,τ) experiences a drop while keeping τ constant.

    Figures 3 and 4 respectively provide surface plots of the horizontal velocity component U(ζ,τ) and the free surface W(ζ,τ) for μ=0.25,0.50,0.75,1, 5ζ5 and 0τ0.1. Based on the data shown in the tables and figures, it can be noticed that there is a strong level of concurrence among all three derivatives. The methodology outlined in this paper elucidates that when the fractional order approaches the classical scenario, the obtained solution likewise converges toward the analytical solution. This finding serves to validate the accuracy of the used scheme. Hence, the tangible manifestation of our findings can potentially serve as a valuable instrument for exploring additional discoveries pertaining to nonlinear wave phenomena in scientific applications.

    We applied the NTDM approach to study the horizontal velocity and free surface of a TFCSSWE arising in ocean engineering. The fractional derivative has been applied from the perspectives of the C, CF and ABC approaches. The analytical solutions derived by using the NTDM approach, according to the results, are relatively close to the precise solutions. According to the tables and graphs, the approximate solution of the differential equation converges to the exact solution when μ=1. The technique presented in this study showcases the validity and efficacy of the implemented method through a comparative analysis of the obtained results with those reported in previous studies. Thus, the proposed approach for obtaining numerical and analytical solutions to nonlinear problems is exceptionally trustworthy and efficient. The subsequent findings illustrate that the suggested methodology is exceptionally effective. The aforementioned methodology exhibits reliability, straightforwardness and innovation in its application to the resolution of fractional- order systems of differential equations. Our findings are expected to make a valuable contribution to future research on the behavior of SWEs in various fields, including mathematical physics, applied mathematics, ocean engineering, civil engineering and port and coastal construction. Further, this method can be used to analyze nonlinear fractional-order mathematical models of infectious diseases like Ebola, hepatitis, tuberculosis and others.

    The authors declare that they have not used artificial Intelligence tools in the creation of this article.

    The authors would like to thank the reviewers for their thorough reading and insightful comments, observations and suggestions that significantly improved the manuscript.

    The authors declare no conflicts of interest.



    [1] V. E. Tarasov, Fractional dynamics: Applications of fractional calculus to dynamics of particles, fields and media, Springer, 2011.
    [2] R. Metzler, J. Klafter, Boundary value problems for fractional diffusion equations, Phys. A, 278 (2000), 107–125. https://doi.org/10.1016/S0378-4371(99)00503-8 doi: 10.1016/S0378-4371(99)00503-8
    [3] A. Din, Y. J. Li, A. Yusuf, Delayed hepatitis B epidemic model with stochastic analysis, Chaos Solitons Fract., 146 (2021), 110839. https://doi.org/10.1016/j.chaos.2021.110839 doi: 10.1016/j.chaos.2021.110839
    [4] Q. T. Ain, A. Khan, M. I. Ullah, M. A. Alqudah, T. Abdeljawad, On fractional impulsive system for methanol detoxification in human body, Chaos Solitons Fract., 160 (2022), 112235. https://doi.org/10.1016/j.chaos.2022.112235 doi: 10.1016/j.chaos.2022.112235
    [5] D. Baleanu, A. Jajarmi, H. Mohammadi, S. Rezapour, A new study on the mathematical modelling of human liver with Caputo-Fabrizio fractional derivative, Chaos Solitons Fract., 134 (2020), 109705. https://doi.org/10.1016/j.chaos.2020.109705 doi: 10.1016/j.chaos.2020.109705
    [6] H. M. Srivastava, K. M. Saad, Some new models of the time-fractional gas dynamics equation, Adv. Math. Models Appl., 3 (2018), 5–17.
    [7] N. D. Phuong, L. V. C. Hoan, E. Karapinar, J. Singh, H. D. Binh, N. H. Can, Fractional order continuity of a time semi-linear fractional diffusion-wave system, Alex. Eng. J., 59 (2020), 4959–4968. https://doi.org/10.1016/j.aej.2020.08.054 doi: 10.1016/j.aej.2020.08.054
    [8] I. Podlubny, Fractional differential equations, Academic Press, 1999.
    [9] S. G. Samko, A. A. Kilbas, O. I. Marichev, Fractional integrals and derivatives, translated from the 1987 Russian original, Yverdon: Gordon and Breach, 1993.
    [10] A. A. Kilbas, H. M. Srivastava, J. J. Trujillo, Theory and applications of fractional differential equations, Elsevier, 2006.
    [11] Y. J. Jiang, J. T. Ma, High-order finite element methods for time-fractional partial differential equations, J. Comput. Appl. Math., 235 (2011), 3285–3290. https://doi.org/10.1016/j.cam.2011.01.011 doi: 10.1016/j.cam.2011.01.011
    [12] D. M. Gusu, D. Wegi, G. Gemechu, D. Gemechu, Fractional order Airy's type differential equations of its models using RDTM, Math. Probl. Eng., 2021 (2021), 1–21. https://doi.org/10.1155/2021/3719206 doi: 10.1155/2021/3719206
    [13] M. Safari, D. D. Ganji, M. Moslemi, Application of He's variational iteration method and Adomian's decomposition method to the fractional KdV-Burgers-Kuramoto equation, Comput. Math. Appl., 58 (2009), 2091–2097. https://doi.org/10.1016/j.camwa.2009.03.043 doi: 10.1016/j.camwa.2009.03.043
    [14] K. S. Nisar, A. Ciancio, K. K. Ali, M. S. Osman, C. Cattani, D. Baleanu, et al., On beta-time fractional biological population model with abundant solitary wave structures, Alex. Eng. J., 61 (2022), 1996–2008. https://doi.org/10.1016/j.aej.2021.06.106 doi: 10.1016/j.aej.2021.06.106
    [15] N. Iqbal, I. Khan, R. Shah, K. Nonlaopon, The fuzzy fractional acoustic waves model in terms of the Caputo-Fabrizio operator, AIMS Math., 8 (2023), 1770–1783. https://doi.org/10.3934/math.2023091 doi: 10.3934/math.2023091
    [16] K. S. Nisar, M. Farman, E. Hincal, A. Shehzad, Modelling and analysis of bad impact of smoking in society with constant proportional-Caputo Fabrizio operator, Chaos Solitons Fract., 172 (2023), 113549. https://doi.org/10.1016/j.chaos.2023.113549 doi: 10.1016/j.chaos.2023.113549
    [17] X. D. Zhang, J. P. Zhao, J. Liu, B. Tang, Homotopy perturbation method for two dimensional time-fractional wave equation, Appl. Math. Model., 38 (2014), 5545–5552. https://doi.org/10.1016/j.apm.2014.04.018 doi: 10.1016/j.apm.2014.04.018
    [18] L. Akinyemi, P. Veeresha, S. O. Ajibola, Numerical simulation for coupled nonlinear Schrödinger-Korteweg-de Vries and Maccari systems of equations, Mod. Phys. Lett. B, 35 (2021), 2150339. https://doi.org/10.1142/S0217984921503395 doi: 10.1142/S0217984921503395
    [19] N. Iqbal, M. T. Chughtai, R. Ullah, Fractional study of the non-linear Burgers' equations via a semi-analytical technique, Fractal Fract., 7 (2023), 1–17. https://doi.org/10.3390/fractalfract7020103 doi: 10.3390/fractalfract7020103
    [20] A. R. Seadawy, D. Kumar, A. K. Chakrabarty, Dispersive optical soliton solutions for the hyperbolic and cubic-quintic nonlinear Schrödinger equations via the extended sinh-Gordon equation expansion method, Eur. Phys. J. Plus, 133 (2018), 182. https://doi.org/10.1140/epjp/i2018-12027-9 doi: 10.1140/epjp/i2018-12027-9
    [21] A. R. Seadawy, N. Cheemaa, Some new families of spiky solitary waves of one-dimensional higher-order K-dV equation with power law nonlinearity in plasma physics, Indian J. Phys, 94 (2020), 117–126. https://doi.org/10.1007/s12648-019-01442-6 doi: 10.1007/s12648-019-01442-6
    [22] J. Singh, D. Kumar, D. Baleanu, S. Rathore, An efficient numerical algorithm for the fractional Drinfeld-Sokolov-Wilson equation, Appl. Math. Comput., 335 (2018), 12–24. https://doi.org/10.1016/j.amc.2018.04.025 doi: 10.1016/j.amc.2018.04.025
    [23] M. Younis, A. R. Seadawy, I. Sikandar, M. Z. Baber, N. Ahmed, S. T. R. Rizvi, et al., Nonlinear dynamical study to time fractional Dullian-Gottwald-Holm model of shallow water waves, Int. J. Mod. Phys. B, 36 (2022), 2250004. https://doi.org/10.1142/S0217979222500047 doi: 10.1142/S0217979222500047
    [24] J. Wang, K. Shehzad, A. R. Seadawy, M. Arshad, F. Asmat, Dynamic study of multi-peak solitons and other wave solutions of new coupled KdV and new coupled Zakharov-Kuznetsov systems with their stability, J. Taibah Univ. Sci., 17 (2023), 2163872. https://doi.org/10.1080/16583655.2022.2163872 doi: 10.1080/16583655.2022.2163872
    [25] A. R. Seadawy, Stability analysis for Zakharov-Kuznetsov equation of weakly nonlinear ion-acoustic waves in a plasma, Comput. Math. Appl., 67 (2014), 172–180. https://doi.org/10.1016/j.camwa.2013.11.001 doi: 10.1016/j.camwa.2013.11.001
    [26] A. R. Seadawy, S. T. R. Rizvi, S. Ahmad, M. Younis, D. Baleanu, Lump, lump-one stripe, multiwave and breather solutions for the Hunter-Saxton equation, Open Phys., 19 (2021), 1–10. https://doi.org/10.1515/phys-2020-0224 doi: 10.1515/phys-2020-0224
    [27] A. Zafar, A. Bekir, B. Khalid, H. Rezazadeh, Abundant solitary wave solutions for the fractional coupled Jaulent-Miodek equations arising in applied physics, Int. J. Mod. Phys. B, 34 (2020), 2050279. https://doi.org/10.1142/S0217979220502793 doi: 10.1142/S0217979220502793
    [28] J. G. Liu, Y. F. Zhang, J. J. Wang, Investigation of the time fractional generalized (2+1)-dimensional Zakharov-Kuznetsov equation with single-power law nonlinearity, Fractals, 31 (2023), 2350033. https://doi.org/10.1142/S0218348X23500330 doi: 10.1142/S0218348X23500330
    [29] J. G. Liu, X. J. Yang, Symmetry group analysis of several coupled fractional partial differential equations, Chaos Solitons Fract., 173 (2023), 113603. https://doi.org/10.1016/j.chaos.2023.113603 doi: 10.1016/j.chaos.2023.113603
    [30] T. Ozer, Symmetry group analysis of Benney system and an application for shallow-water equations, Mech. Res. Commun., 32 (2005), 241–254. https://doi.org/10.1016/j.mechrescom.2004.10.002 doi: 10.1016/j.mechrescom.2004.10.002
    [31] S. Kumar, A. Kumar, Z. Odibat, M. Aldhaifallah, K. S. Nisar, A comparison study of two modified analytical approach for the solution of nonlinear fractional shallow water equations in fluid flow, AIMS Math., 5 (2020), 3035–3055. https://doi.org/10.3934/math.2020197 doi: 10.3934/math.2020197
    [32] S. J. Liang, J. H. Tang, M. S. Wu, Solution of shallow-water equations using least-squares finite-element method, Acta Mech. Sin., 24 (2008), 523–532. https://doi.org/10.1007/s10409-008-0151-4 doi: 10.1007/s10409-008-0151-4
    [33] S. Kumar, A numerical study for the solution of time fractional nonlinear shallow water equation in oceans, Z. Naturforschung A, 68 (2013), 547–553. https://doi.org/10.5560/zna.2013-0036 doi: 10.5560/zna.2013-0036
    [34] N. Ali, M. F. Yassen, S. A. Asiri, R. Nawaz, L. Zada, M. M. Alam, N. Sene, New iterative method for solving a coupled system of fractional-order Drinfeld-Sokolov-Wilson (FDSW) and fractional shallow water (FSW) equations, J. Nanomater, 2022 (2022), 1–13. https://doi.org/10.1155/2022/8370107 doi: 10.1155/2022/8370107
    [35] M. Rawashdeh, S. Maitama, Finding exact solutions of nonlinear PDEs using the natural decomposition method, Math. Methods Appl. Sci., 40 (2017), 223–236. https://doi.org/10.1002/mma.3984 doi: 10.1002/mma.3984
    [36] M. X. Zhou, A. S. V. R. Kanth, K. Aruna, K. Raghavendar, H. Rezazadeh, M. Inc, et al., Numerical solutions of time fractional Zakharov-Kuznetsov equation via natural transform decomposition method with nonsingular kernel derivatives, J. Funct. Spaces, 2021 (2021), 1–17. https://doi.org/10.1155/2021/9884027 doi: 10.1155/2021/9884027
    [37] A. S. V. R. Kanth, K. Aruna, K. Raghavendar, H. Rezazadeh, M. Inc, Numerical solutions of nonlinear time fractional Klein-Gordon equation via natural transform decomposition method and iterative Shehu transform method, J. Ocean Eng. Sci., 2021. https://doi.org/10.1016/j.joes.2021.12.002 doi: 10.1016/j.joes.2021.12.002
    [38] P. Koppala, R. Kondooru, An efficient technique to solve time-fractional Kawahara and modified Kawahara equations, Symmetry, 14 (2022), 1777. https://doi.org/10.3390/sym14091777 doi: 10.3390/sym14091777
    [39] K. Pavani, K. Raghavendar, Approximate solutions of time-fractional Swift-Hohenberg equation via natural transform decomposition method, Int. J. Appl. Comput. Math., 9 (2023), 29. https://doi.org/10.1007/s40819-023-01493-8 doi: 10.1007/s40819-023-01493-8
    [40] M. Caputo, Elasticita e dissipazione, Bologna: Zanichelli, 1969.
    [41] J. Losada, J. J. Nieto, Properties of a new fractional derivative without singular kernel, Progr. Fract. Differ. Appl., 1 (2015), 87–92.
    [42] A. Atangana, I. Koca, Chaos in a simple nonlinear system with Atangana-Baleanu derivatives with fractional order, Chaos Solitons Fract., 89 (2016), 447–454. https://doi.org/10.1016/j.chaos.2016.02.012 doi: 10.1016/j.chaos.2016.02.012
    [43] D. G. Prakasha, P. Veeresha, M. S. Rawashdeh, Numerical solution for (2+1)‐dimensional time‐fractional coupled Burger equations using fractional natural decomposition method, Math. Methods Appl. Sci., 42 (2019), 3409–3427. https://doi.org/10.1002/mma.5533 doi: 10.1002/mma.5533
    [44] R. K. A. S. Venkata, A. Kirubanandam, R. Kondooru, Numerical solutions of time fractional Sawada Kotera Ito equation via natural transform decomposition method with singular and nonsingular kernel derivatives, Math. Methods Appl. Sci., 44 (2021), 14025–14040. https://doi.org/10.1002/mma.7672 doi: 10.1002/mma.7672
    [45] A. Khalouta, A. Kadem, A new numerical technique for solving fractional Bratu's initial value problems in the Caputo and Caputo-Fabrizio sense, J. Appl. Math. Comput. Mech., 19 (2020), 43–56. https://doi.org/10.17512/jamcm.2020.1.04 doi: 10.17512/jamcm.2020.1.04
    [46] A. S. V. R. Kanth, K. Aruna, K. Raghavendar, Natural transform decomposition method for the numerical treatment of the time fractional Burgers-Huxley equation, Numer. Methods Partial Differ. Equ., 39 (2023), 2690–2718. https://doi.org/10.1002/num.22983 doi: 10.1002/num.22983
  • This article has been cited by:

    1. Joseph Sultana, Approximating photon trajectories in spherically symmetric spacetimes, 2024, 56, 0001-7701, 10.1007/s10714-024-03274-0
    2. Hegagi Mohamed Ali, Analytical investigation of the fractional nonlinear shallow-water model, 2024, 1598-5865, 10.1007/s12190-024-02172-7
    3. Newton I. Okposo, K. Raghavendar, Naveed Khan, J. F. Gómez-Agullar, Abel M. Jonathan, New exact optical solutions for the Lakshmanan–Porsezian–Daniel equation with parabolic law nonlinearity using the ϕ6
    -expansion technique, 2024, 0924-090X, 10.1007/s11071-024-10430-3
    4. K. Pavani, K. Raghavendar, K. Aruna, Solitary wave solutions of the time fractional Benjamin Bona Mahony Burger equation, 2024, 14, 2045-2322, 10.1038/s41598-024-65471-w
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1733) PDF downloads(107) Cited by(4)

Figures and Tables

Figures(4)  /  Tables(6)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog