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An accurate approach based on the orthonormal shifted discrete Legendre polynomials for variableorder fractional Sobolev equation
Advances in Difference Equations volume 2021, Article number: 272 (2021)
Abstract
This paper applies the Heydari–Hosseininia nonsingular fractional derivative for defining a variableorder fractional version of the Sobolev equation. The orthonormal shifted discrete Legendre polynomials, as an appropriate family of basis functions, are employed to generate an operational matrix method for this equation. A new fractional operational matrix related to these polynomials is extracted and employed to construct the presented method. Using this approach, an algebraic system of equations is obtained instead of the original variableorder equation. The numerical solution of this system can be found easily. Some numerical examples are provided for verifying the accuracy of the generated approach.
Introduction
Over the past decades, the subject of fractional calculus (as a generalization of the classical calculus) has been widely studied [1–3]. In fact, fractional derivative and integral operators, due to higher degree of freedom in comparison to the classical operators as well as their memory and nonlocal properties, have received many applications in various problems [4]. For instance, some important works related to recent developments in fractional calculus and its applications can be found in [5–10]. The reader should note that the most important issue about problems involving such operators is finding their exact solutions, which is often very difficult and may even be impossible. This fact has led to the use of numerical methods as a convenient alternative to solve this drawback. Some numerical methods that have recently been applied to solve such problems can be found in [11–18].
Given that the order of fractional operators is permissible to take any value, a more general generalization is that the order of fractional operators be a definite function of the variables in the problem [19]. In fact, fractional operators of variable order (VO) can be utilized for more accurate modeling of realworld phenomena [20, 21]. The remarkable point about such operators is that their memory property is more evident [22]. Some problems that have recently been modeled by such operators can be found in [23, 24]. However, similar to constantorder fractional equations, the major challenge in dealing with VO fractional equations is finding their analytical solutions, which is often impossible. For this reason, in recent years, many numerical approaches have been constructed to solve this category of problems. For instances, see [25–29].
The Sobolev equation is a wellstudied partial differential equation which has been frequently utilized in the fluid dynamics to express the fluid motion through rock or soil, and other media [30]. This equation is a special form of the Benjamin–Bona–Mahony–Burgers problem, where the coefficients of nonlinear term and both firstorder derivatives are zero [31]. Many applications of the Sobolev equation have been reported in moisture migration in soil [32], thermodynamics [33], and fluid motion [33]. There are many approaches that have been applied to solve various types of the Sobolev equation in recent years. For instances, see [30, 31, 34–37].
Recently, the author of [38] introduced a new nonsingular VO fractional derivative, where the MittagLeffler function is its kernel. As far as we know, there is no previous VO fractional version of the Sobolev problem. This motivates us to pursue the following goals:

Defining a VO fractional prescription of the Sobolev equation using the nonsingular fractional derivative expressed in [38].

Constructing a highly accurate method based upon the orthonormal shifted discrete Legendre polynomials (DLPs) for this equation.
So, we concentrate on the problem
under the initial and boundary conditions
where \(\theta (\cdot,\cdot)\) is the undetermined solution, μ and ν are positive constants, \(\zeta (\cdot)\) is a continuous function in its domain, and \(\varphi (\cdot,\cdot)\), \(\hat{\theta }(\cdot)\), \(\tilde{\theta }_{0}(\cdot)\), and \(\tilde{\theta }_{1}(\cdot)\) are given functions. Also, \({}^{HH}_{0}{\partial _{\tau }^{\zeta (\tau )}}\theta (y,\tau )\) is the VO fractional derivative of order \(\zeta (\tau )\) with respect to τ in the Heydari–Hosseininia (HH) sense of the functions \(\theta (y,\tau )\) [38]. This equation can have useful applications in many applied problems, such as the transport phenomena of humidity in soil, the heat conduction phenomena in different media, and the porous theories concerned with percolation into rocks with cracks. Note that in the case of \(\zeta (\tau )=1\), this problem reduces to the classical Sobolev problem.
One good idea for solving fractional functional equations is employing polynomials as basis functions to construct numerical methods. This is important for two reasons: First, the computation of the fractional derivative and integral of these functions is easy; and second, if the solution of the problem under study is sufficiently smooth, highprecision solutions can be achieved. Basis orthogonal polynomials are classified into discrete and continuous kinds regarding the method of calculating their expansion coefficients [39]. Unlike continuous polynomials, the expansion coefficients of which are calculated by integrating (in most cases numerically), the expansion coefficients of discrete polynomials are calculated accurately using a finite summation. In recent years, discrete polynomials have been extensively applied for solving diverse problems. For instances, see [39–47].
This study applies the orthonormal shifted DLPs for solving the Sobolev equation (1.1) subject to conditions (1.2). To this end, a new fractional matrix related to the VO fractional differentiation of these polynomials is obtained and applied for generating a numerical technique for this problem. The intended approach is constructed using these polynomials expansion and the tau technique. This technique converts the VO fractional problem into an algebraic system of equations that readily can be handled. Note that since it is easier to obtain the operation matrix of VO fractional derivative of the orthonormal shifted DLPs than continuous polynomials, we have considered these discrete polynomials as basis functions for solving this VO fractional problem.
Organization of this article is as follows: The VO fractional derivative in the HH sense is reviewed in Sect. 2. The orthonormal shifted DLPs are reviewed in Sect. 3. Some matrix equalities are obtained in Sect. 4. The computational approach is explicated in Sect. 5. Numerical examples are given in Sect. 6. Conclusion of this study is provided in Sect. 7.
Preliminaries
Here, we review the definition of the VO fractional differentiation used in this study. First of all, we express the definition of the MittagLeffler function that is given in [4] by
Please remember that for \(b=1\) it is considered as \(\textbf{E}_{a}(\tau )=\textbf{E}_{a,1}(\tau )\). The VO fractional derivative of order \(\zeta (\tau )\in (0,1)\) (where \(\zeta (\tau )\) is a continuous function on its domain) in the HH sense of the function \(\theta (\tau )\) is given in [38] as follows:
The above definition results in
where \(r\in \mathbb{Z}^{+}\bigcup \{0\}\).
Orthonormal shifted discrete Legendre polynomials
The orthonormal shifted DLPs are defined over \([0,\tau _{b} ]\) as follows [44]:
where
\(S_{k}^{(m)}\)s are the first type Stirling numbers,
and \(\binom{i}{k}\) is the binomial coefficient. These polynomials can be utilized for approximating any continuous function \(\theta (\tau )\) over \([0,\tau _{b} ]\) as follows:
where
in which
and
Likely, a continuous function \(\theta (y,\tau )\) defined over \([0,y_{b} ]\times [0,\tau _{b} ]\) can be approximated by the orthonormal shifted DLPs as
in which \(\boldsymbol{\Theta }=[\theta _{(i1)(j1)}]\) is a matrix with \((M+1)\times (N+1)\) entries as
Matrix relationships
Here and in what follows, we give some matrix relationships related to the orthonormal shifted DLPs.
Theorem 4.1
([44])
Differentiation of the vector \(\Psi _{\tau _{b}, N}(\tau )\) introduced in (3.6) satisfies the relation
where \(\mathbf{D}_{N}^{ (1,\tau _{b} )}= [d_{ij}^{ (1, \tau _{b} )} ]\) is a matrix of order \((N+1)\) with entries
Moreover, for any integer n, we have
Theorem 4.2
Suppose that \(\zeta : [0,\tau _{b} ]\longrightarrow (0,1)\) is a given continuous function and \(\Psi _{\tau _{b}, N}(\tau )\) is the vector expressed in (3.7). Then we have
where \(\mathbf{Q}_{N}^{ (\zeta ,\tau _{b} )}= [q_{ij}^{ (\zeta ,\tau _{b} )} ]\) is a matrix of order \((N+1)\) with entries
in which
Proof
Regarding (2.3), we have \({}^{HH}_{0}{D_{\tau }^{\zeta (\tau )}} L_{\tau _{b}, 0} ( \tau ;N )=0\). So, in the matrix \(\mathbf{Q}_{N}^{ (\zeta ,\tau _{b} )}\), the first row should be zero. Assume \(\hat{i}\geq 1\) and \(\zeta : [0,\tau _{b} ]\longrightarrow (0,1)\) be a continuous function. From (2.3) and (3.1), we get
The above result can be approximated as
where, regarding (3.5), we have
Eventually, via the change of indices \(\hat{i}=i1\) and \(\hat{j}=j1\), and considering \(q_{ij}^{ (\zeta ,\tau _{b} )}\) instead of \(\hat{q}_{i1 j1}^{ (\zeta ,\tau _{b} )}\), we obtain
for \(2\leq i\leq N+1\) and \(1\leq j\leq N+1\). Thus, the expressed claim is proved. □
For example, whenever \(\zeta (\tau )=0.5+0.25\sin (\tau )\), we obtain
Computational method
In order to use the orthonormal shifted DLPs for problem (1.1) with initial and boundary conditions (1.2), we express the unknown solution as
where Θ is an \((M+1)\times (N+1)\) matrix, and its elements are undetermined. Theorem 4.1 results in
Besides, Theorem 4.2 together with the above relations yields
and
In addition, we represent \(\varphi (y,\tau )\) using the orthonormal shifted DLPs as follows:
where Φ is an \((M+1)\times (N+1)\) given matrix, and its elements are evaluated like in (3.8). By inserting (5.2)–(5.5) into (1.1), we obtain
The functions given in (1.2) can also be approximated via the orthonormal shifted DLPs as
and
in which \(\hat{\boldsymbol{\Theta }}\) is an \((M+1)\)order column vector, \(\tilde{\boldsymbol{\Theta }}_{0}\) and \(\tilde{\boldsymbol{\Theta }}_{1}\) are \((N+1)\)order column vectors, and their elements are evaluated like in (3.5). Now, from (1.2), (5.1), (5.7), and (5.8), we obtain
and
Utilizing (5.6), (5.9), and (5.10), we generate the following system:
Finally, by solving (5.11) and finding the elements of the matrix Θ, we find a numerical solution for the primary VO fractional problem by inserting Θ into (5.1).
Numerical examples
The approach generated using the orthonormal shifted DLPs is applied in this section for solving some numerical examples. The \(L_{2}\)error of the numerical results is measured as
where θ and θ̃ are the analytic and numerical solutions, respectively. The convergence order (CO) of this approach is computed as follows:
where \(\varepsilon _{i}\) and \(\varepsilon _{2}\) are the first and second \(L_{2}\)error values, respectively. Furthermore, \(\bar{N}_{i}=(M_{i}+1)\times (N_{i}+1)\) for \(i=1, 2\) is the number of the orthonormal shifted DLPs utilized in the ith implementation. In addition, we have applied Maple 18 (with 15 digits precision) for obtaining the results. Meanwhile, the series generating the MittagLeffler function is applied for 25 terms.
Example 1
Consider problem (1.1) on \([0,3]\times [0,1]\) with \(\mu =\nu =1\) and
This example has the analytic solution
So, we have
We have applied the expressed method for this example with three choices of \(\zeta (\tau )\). The extracted results are listed in Table 1. This table shows the highprecision of the proposed approach in solving this example. It also confirms that the results have a high degree of convergence. The last column of this table confirms the low computational works of the presented algorithm. Graphical behaviors of the extracted results for \(\zeta (\tau )=0.50+0.25\sin (\tau )\) where \((M=9,N=8)\) are illustrated in Fig. 1. This figure shows the high accuracy of the presented method for obtaining a smooth solution for this example.
Example 2
Consider problem (1.1) on \([0,1]\times [0,2]\) with \(\mu =\frac{1}{2}\), \(\nu =1\) and
This example has the analytic solution
Thus, we have
The technique established upon the orthonormal shifted DLPs is implemented for this example. The gained results are provided in Table 2, and they confirm the highprecision and low computations of the approach. It can also be seen that as the number of the orthonormal shifted DLPs increases, the accuracy of the results increases rapidly. The obtained results with \((M=N=8)\) whenever \(\zeta (\tau )=0.65+0.25\tau ^{3}\cos (\tau )\) are shown in Fig. 2. This figure illustrates that the proposed method can provide a highly accurate solution for this example across the domain.
Conclusion
In this study, the Heydari–Hosseininia fractional differentiation as a kind of nonsingular variableorder (VO) fractional derivative was utilized for generating a VO fractional version of the Sobolev equation. The orthonormal shifted discrete Legendre polynomials (DLPs) as a convenient family of basis functions were employed to generate a numerical algorithm for this equation. A new fractional operational matrix related to VO fractional differentiation of these polynomials was obtained. The established scheme converts solving the problem under consideration into solving an algebraic system of equations. The validity of this technique was investigated by solving two numerical examples. The obtained results confirmed that the established method is able to generate numerical solutions with high accuracy for such problems even by applying a small number of the orthonormal shifted DLPs. As future research direction, the VO fractional derivative applied in this study can be utilized for generating VO fractional version of other applicable problems, such as Schrödinger equation and advectiondiffusion equation.
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References
 1.
Baleanu, D., Ghanbari, B., Asad, J., Jajarmi, A., Mohammadi Pirouz, H.: Planar systemmasses in an equilateral triangle: numerical study within fractional calculus. Comput. Model. Eng. Sci. 124(3), 953–968 (2020)
 2.
Sadat Sajjadi, S., Baleanu, D., Jajarmi, A., Mohammadi Pirouz, H.: A new adaptive synchronization and hyperchaos control of a biological snap oscillator. Chaos Solitons Fractals 138, 109919 (2020)
 3.
Baleanu, D., Jajarmi, A., Sadat Sajjadi, S., Asad, J.H.: The fractional features of a harmonic oscillator with positiondependent mass. Commun. Theor. Phys. 72(5), 055002 (2020)
 4.
Podlubny, I.: Fractional Differential Equations: An Introduction to Fractional Derivatives, Fractional Differential Equations, to Methods of Their Solution and Some of Their Applications. Elsevier, Amsterdam (1998)
 5.
Rouzegar, J., Vazirzadeh, M., Heydari, M.H.: A fractional viscoelastic model for vibrational analysis of thin plate excited by supports movement. Mech. Res. Commun. 110, 103618 (2020)
 6.
Li, M.: Multifractional generalized Cauchy process and its application to teletraffic. Physica A (2020). https://doi.org/10.1016/j.physa.2019.123982
 7.
Li, M.: Three classes of fractional oscillators, symmetryBasel. Symmetry 10(2), 40 (2018)
 8.
ElShahed, M., Nieto, J.J., Ahmed, A.: Fractionalorder model for biocontrol of the lesser date moth in palm trees and its discretization. Adv. Differ. Equ. 2017, 295 (2017)
 9.
Veeresha, P., Prakasha, D.G., Singh, J., Kumar, D., Baleanu, D.: Fractional KleinGordonSchrödinger equations with MittagLeffler memory. Chin. J. Phys. 68, 65–78 (2020)
 10.
Veeresha, P., Prakasha, D.G., Singh, J., Kumar, D., Baleanu, D.: Analysis of fractional blood alcohol model with composite fractional derivative. Chaos Solitons Fractals 140, 110127 (2020)
 11.
Azin, H., Mohammadi, F., Heydari, M.H.: A hybrid method for solving time fractional advection–diffusion equation on unbounded space domain. Adv. Differ. Equ. 2020(1), 1 (2020)
 12.
Hooshmandasl, M.R., Heydari, M.H., Cattani, C.: Numerical solution of fractional subdiffusion and timefractional diffusionwave equations via fractionalorder Legendre functions. Eur. Phys. J. Plus 131(8), 1–22 (2016)
 13.
Do, Q.H., Ngo, H.T.B., Razzaghi, M.: A generalized fractionalorder Chebyshev wavelet method for twodimensional distributedorder fractional differential equations. Commun. Nonlinear Sci. Numer. Simul. 95, 105597 (2021)
 14.
Singh, J., Kumar, D., Purohit, S.D., Mishra, A.M., Bohra, M.: An efficient numerical approach for fractional multidimensional diffusion equations with exponential memory. Numer. Methods Partial Differ. Equ. 37(2), 1631–1651 (2021)
 15.
Srivastava, H.M., Dubey, V.P., Kumare, R., Singh, J., Kumar, D., Baleanu, D.: An efficient computational approach for a fractionalorder biological population model with carrying capacity. Chaos Solitons Fractals 138, 109880 (2020)
 16.
Singh, J., Ahmadian, A., Rathore, S., Kumar, D., Baleanu, D., Salimi, M., Salahshour, S.: An efficient computational approach for local fractional Poisson equation in fractal media. Numer. Methods Partial Differ. Equ. 37, 1439–1448 (2021)
 17.
Liu, J.G., Yang, X.J., Feng, Y.Y., Cui, P.: On group analysis of the time fractional extended (2 + 1)dimensional ZakharovKuznetsov equation in quantum magnetoplasmas. Math. Comput. Simul. 178, 407–421 (2020)
 18.
Liu, J.G., Yang, X.J., Feng, Y.Y., Cui, P., Gengab, L.L.: On integrability of the higher dimensional time fractional KdVtype equation. J. Geom. Phys. 160, 104000 (2021)
 19.
Coimbra, C.F.M.: Mechanics with variableorder differential operators. Ann. Phys. 12(11–12), 692–703 (2003)
 20.
Kobelev, Y.L., Klimontovich, Y.L.: Statistical physics of dynamic systems with variable memory. Dokl. Phys. 48, 285–289 (2003)
 21.
Sun, H.G., Chen, W., Chen, Y.Q.: Variable order fractional differential operators in anomalous diffusion modeling. Physica A 21, 4586–45920 (2009)
 22.
Heydari, M.H., Avazzadeh, Z., Yang, Y., Cattani, C.: A cardinal method to solve coupled nonlinear variableorder time fractional sineGordon equations. Comput. Appl. Math. 39(2) (2020)
 23.
Hosseininia, M., Heydari, M.H., Roohi, R., Avazzadeh, Z.: A computational wavelet method for variableorder fractional model of dual phase lag bioheat equat. J. Comput. Phys. 395, 1–18 (2019)
 24.
Roohi, R., Hosseininia, M., Heydari, M.H.: A wavelet approach for the variableorder fractional model of ultrashort pulsed laser therapy. Eng. Comput. (2021). https://doi.org/10.1007/s0036602101367x
 25.
Babaei, A., Jafari, H., Banihashemi, S.: Numerical solution of variable order fractional nonlinear quadratic integrodifferential equations based on the sixthkind Chebyshev collocation method. J. Comput. Appl. Math. 377, 112908 (2020)
 26.
Heydari, M.H., Avazzadeh, Z.: Orthonormal Bernstein polynomials for solving nonlinear variableorder time fractional fourthorder diffusionwave equation with nonsingular fractional derivative. Math. Methods Appl. Sci. (2020). https://doi.org/10.1002/mma.6483
 27.
Hassani, H., Avazzadeh, Z., Tenreiro Machado, J.A.: Solving twodimensional variableorder fractional optimal control problems with transcendental Bernstein series. J. Comput. Nonlinear Dyn. 14(6), 061001 (2019)
 28.
Heydari, M.H., Avazzadeh, Z.: New formulation of the orthonormal Bernoulli polynomials for solving the variableorder time fractional coupled BoussinesqBurger’s equations. Eng. Comput. (2020). https://doi.org/10.1007/s0036602001007w
 29.
Hosseininia, M., Heydari, M.H., Avazzadeh, Z.: Numerical study of the variableorder fractional version of the nonlinear fourthorder 2D diffusionwave equation via 2D Chebyshev wavelets. Eng. Comput. (2020). https://doi.org/10.1007/s0036602000995z
 30.
Nikan, O., Avazzadeh, Z.: A localisation technique based on radial basis function partition of unity for solving Sobolev equation arising in fluid dynamics. Appl. Math. Comput. 401, 126063 (2021)
 31.
Abbaszadeh, M., Dehghan, M.: Interior penalty discontinuous Galerkin technique for solving generalized Sobolev equation. Appl. Numer. Math. 154, 172–186 (2020)
 32.
Barenblatt, G.I., Zheltov, I.P., Kochina, I.: Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks strata. J. Appl. Math. Mech. 24(5), 1286–1303 (1960)
 33.
Ting, T.W.: A cooling process according to twotemperature theory of heat conduction. J. Math. Anal. Appl. 45(1), 23–31 (1974)
 34.
Dehghan, M., Shafieeabyaneh, N., Abbaszadeh, M.: Application of spectral element method for solving Sobolev equations with error estimation. Appl. Numer. Math. 58, 439–462 (2020)
 35.
Haq, S., Ghafoor, A., Hussain, M., Arifeen, S.: Numerical solutions of two dimensional Sobolev and generalized BenjaminBonaMahonyBurgers equations via Haar wavelets. Comput. Math. Appl. 72(2), 565–575 (2019)
 36.
Oruç, O.: A computational method based on Hermite wavelets for twodimensional Sobolev and regularized long wave equations in fluids. Numer. Methods Partial Differ. Equ. 34(5), 1693–1715 (2018)
 37.
Liu, J., Li, H., Liu, Y.: CrankNicolson finite element scheme and modified reducedorder scheme for fractional Sobolev equation. Numer. Funct. Anal. Optim. 39(15), 1635–1655 (2018)
 38.
Heydari, M.H., Hosseininia, M.: A new variableorder fractional derivative with nonsingular MittagLeffler kernel: application to variableorder fractional version of the 2D Richard equation. Eng. Comput. (2020). https://doi.org/10.1007/s00366020011219
 39.
Moradi, L., Mohammadi, F.: A discrete orthogonal polynomials approach for coupled systems of nonlinear fractional order integrodifferential equations. Tbil. Math. J. 12(3), 21–38 (2019)
 40.
Gong, D., Wang, X., Wu, S., Zhu, X.: Discrete Legendre polynomialsbased inequality for stability of timevarying delayed systems. J. Franklin Inst. 356, 9907–9927 (2019)
 41.
Salehi, F., Saeedi, H., Moghadam Moghadam, M.: A Hahn computational operational method for variable order fractional mobileimmobile advectiondispersion equation. Math. Sci. 12, 91–101 (2018)
 42.
Salehi, F., Saeeidi, H., Mohseni Moghadam, M.: Discrete Hahn polynomials for numerical solution of twodimensional variableorder fractional RayleighStokes problem. Comput. Appl. Math. 37, 5274–5292 (2018)
 43.
Heydari, M.H., Avazzadeh, Z.: Numerical study of nonsingular variableorder time fractional coupled Burgers’ equations by using the Hahn polynomials. Eng. Comput. (2020). https://doi.org/10.1007/s00366020010365
 44.
Heydari, M.H., Avazzadeh, Z., Atangana, A.: Orthonormal shifted discrete Legendre polynomials for solving a coupled system of nonlinear variableorder time fractional reactionadvectiondiffusion equations. Appl. Numer. Math. 161, 425–436 (2021)
 45.
Heydari, M.H., Avazzadeh, Z., Cattani, C.: Discrete Chebyshev polynomials for nonsingular variableorder fractional KdV Burgers’ equation. Appl. Numer. Math. 44(2), 2158–2170 (2021)
 46.
Heydari, M.H., Razzaghi, M., Avazzadeh, Z.: Orthonormal shifted discrete Chebyshev polynomials: application for a fractalfractional version of the coupled SchrödingerBoussinesq system. Chaos Solitons Fractals 143, 110570 (2021)
 47.
Heydari, M.H., Avazzadeh, Z., Cattani, C.: Numerical solution of variableorder spacetime fractional KdVBurgersKuramoto equation by using discrete Legendre polynomials. Eng. Comput. (2020). https://doi.org/10.1007/s0036602001181x
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Heydari, M.H., Atangana, A. An accurate approach based on the orthonormal shifted discrete Legendre polynomials for variableorder fractional Sobolev equation. Adv Differ Equ 2021, 272 (2021). https://doi.org/10.1186/s13662021034292
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Keywords
 Variableorder time fractional Sobolev equation
 Orthonormal shifted discrete Legendre polynomials
 Nonsingular variableorder fractional derivative