66 research outputs found

    Solutions of fractional gas dynamics equation by a new technique

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    [EN] In this paper, a novel technique is formed to obtain the solution of a fractional gas dynamics equation. Some reproducing kernel Hilbert spaces are defined. Reproducing kernel functions of these spaces have been found. Some numerical examples are shown to confirm the efficiency of the reproducing kernel Hilbert space method. The accurate pulchritude of the paper is arisen in its strong implementation of Caputo fractional order time derivative on the classical equations with the success of the highly accurate solutions by the series solutions. Reproducing kernel Hilbert space method is actually capable of reducing the size of the numerical work. Numerical results for different particular cases of the equations are given in the numerical section.This research was partially supported by Spanish Ministerio de Ciencia, Innovacion y Universidades PGC2018-095896-B-C22 and Generalitat Valenciana PROMETEO/2016/089.Akgül, A.; Cordero Barbero, A.; Torregrosa Sánchez, JR. (2020). Solutions of fractional gas dynamics equation by a new technique. Mathematical Methods in the Applied Sciences. 43(3):1349-1358. https://doi.org/10.1002/mma.5950S13491358433Singh, J., Kumar, D., & Kılıçman, A. (2013). Homotopy Perturbation Method for Fractional Gas Dynamics Equation Using Sumudu Transform. Abstract and Applied Analysis, 2013, 1-8. doi:10.1155/2013/934060Momani, S. (2005). Analytic and approximate solutions of the space- and time-fractional telegraph equations. Applied Mathematics and Computation, 170(2), 1126-1134. doi:10.1016/j.amc.2005.01.009Hajipour, M., Jajarmi, A., Baleanu, D., & Sun, H. (2019). On an accurate discretization of a variable-order fractional reaction-diffusion equation. Communications in Nonlinear Science and Numerical Simulation, 69, 119-133. doi:10.1016/j.cnsns.2018.09.004Meng, R., Yin, D., & Drapaca, C. S. (2019). Variable-order fractional description of compression deformation of amorphous glassy polymers. Computational Mechanics, 64(1), 163-171. doi:10.1007/s00466-018-1663-9Baleanu, D., Jajarmi, A., & Hajipour, M. (2018). On the nonlinear dynamical systems within the generalized fractional derivatives with Mittag–Leffler kernel. Nonlinear Dynamics, 94(1), 397-414. doi:10.1007/s11071-018-4367-yJajarmi, A., & Baleanu, D. (2018). A new fractional analysis on the interaction of HIV withCD4+T-cells. Chaos, Solitons & Fractals, 113, 221-229. doi:10.1016/j.chaos.2018.06.009Baleanu, D., Jajarmi, A., Bonyah, E., & Hajipour, M. (2018). New aspects of poor nutrition in the life cycle within the fractional calculus. Advances in Difference Equations, 2018(1). doi:10.1186/s13662-018-1684-xJajarmi, A., & Baleanu, D. (2017). Suboptimal control of fractional-order dynamic systems with delay argument. Journal of Vibration and Control, 24(12), 2430-2446. doi:10.1177/1077546316687936Singh, J., Kumar, D., & Baleanu, D. (2018). On the analysis of fractional diabetes model with exponential law. Advances in Difference Equations, 2018(1). doi:10.1186/s13662-018-1680-1Kumar, D., Singh, J., Tanwar, K., & Baleanu, D. (2019). A new fractional exothermic reactions model having constant heat source in porous media with power, exponential and Mittag-Leffler laws. International Journal of Heat and Mass Transfer, 138, 1222-1227. doi:10.1016/j.ijheatmasstransfer.2019.04.094Kumar, D., Singh, J., Al Qurashi, M., & Baleanu, D. (2019). A new fractional SIRS-SI malaria disease model with application of vaccines, antimalarial drugs, and spraying. Advances in Difference Equations, 2019(1). doi:10.1186/s13662-019-2199-9Kumar, D., Singh, J., Purohit, S. D., & Swroop, R. (2019). A hybrid analytical algorithm for nonlinear fractional wave-like equations. Mathematical Modelling of Natural Phenomena, 14(3), 304. doi:10.1051/mmnp/2018063Kumar, D., Tchier, F., Singh, J., & Baleanu, D. (2018). An Efficient Computational Technique for Fractal Vehicular Traffic Flow. Entropy, 20(4), 259. doi:10.3390/e20040259Goswami, A., Singh, J., Kumar, D., & Sushila. (2019). An efficient analytical approach for fractional equal width equations describing hydro-magnetic waves in cold plasma. Physica A: Statistical Mechanics and its Applications, 524, 563-575. doi:10.1016/j.physa.2019.04.058Mohyud-Din, S. T., Bibi, S., Ahmed, N., & Khan, U. (2018). Some exact solutions of the nonlinear space–time fractional differential equations. Waves in Random and Complex Media, 29(4), 645-664. doi:10.1080/17455030.2018.1462541Momani, S., & Shawagfeh, N. (2006). Decomposition method for solving fractional Riccati differential equations. Applied Mathematics and Computation, 182(2), 1083-1092. doi:10.1016/j.amc.2006.05.008Hashim, I., Abdulaziz, O., & Momani, S. (2009). Homotopy analysis method for fractional IVPs. Communications in Nonlinear Science and Numerical Simulation, 14(3), 674-684. doi:10.1016/j.cnsns.2007.09.014Yıldırım, A. (2010). He’s homotopy perturbation method for solving the space- and time-fractional telegraph equations. International Journal of Computer Mathematics, 87(13), 2998-3006. doi:10.1080/00207160902874653Momani, S., & Odibat, Z. (2007). Numerical comparison of methods for solving linear differential equations of fractional order. Chaos, Solitons & Fractals, 31(5), 1248-1255. doi:10.1016/j.chaos.2005.10.068Rida, S. Z., El-Sayed, A. M. A., & Arafa, A. A. M. (2010). On the solutions of time-fractional reaction–diffusion equations. Communications in Nonlinear Science and Numerical Simulation, 15(12), 3847-3854. doi:10.1016/j.cnsns.2010.02.007Machado, J. A. T., & Mata, M. E. (2014). A fractional perspective to the bond graph modelling of world economies. Nonlinear Dynamics, 80(4), 1839-1852. doi:10.1007/s11071-014-1334-0Raja Balachandar, S., Krishnaveni, K., Kannan, K., & Venkatesh, S. G. (2018). Analytical Solution for Fractional Gas Dynamics Equation. National Academy Science Letters, 42(1), 51-57. doi:10.1007/s40009-018-0662-xWang, Y.-L., Liu, Y., Li, Z., & zhang, H. (2018). Numerical solution of integro-differential equations of high-order Fredholm by the simplified reproducing kernel method. International Journal of Computer Mathematics, 96(3), 585-593. doi:10.1080/00207160.2018.1455091Gumah, G. N., Naser, M. F. M., Al-Smadi, M., & Al-Omari, S. K. (2018). Application of reproducing kernel Hilbert space method for solving second-order fuzzy Volterra integro-differential equations. Advances in Difference Equations, 2018(1). doi:10.1186/s13662-018-1937-8Al-Smadi, M. (2018). Simplified iterative reproducing kernel method for handling time-fractional BVPs with error estimation. Ain Shams Engineering Journal, 9(4), 2517-2525. doi:10.1016/j.asej.2017.04.006Kashkari, B. S. H., & Syam, M. I. (2018). Reproducing Kernel Method for Solving Nonlinear Fractional Fredholm Integrodifferential Equation. Complexity, 2018, 1-7. doi:10.1155/2018/2304858Akgül, A., & Grow, D. (2019). Existence of Unique Solutions to the Telegraph Equation in Binary Reproducing Kernel Hilbert Spaces. Differential Equations and Dynamical Systems, 28(3), 715-744. doi:10.1007/s12591-019-00453-3Akgül, A., Khan, Y., Akgül, E. K., Baleanu, D., & Al Qurashi, M. M. (2017). Solutions of nonlinear systems by reproducing kernel method. The Journal of Nonlinear Sciences and Applications, 10(08), 4408-4417. doi:10.22436/jnsa.010.08.33Karatas Akgül, E. (2018). Reproducing kernel Hilbert space method for solutions of a coefficient inverse problem for the kinetic equation. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 8(2), 145-151. doi:10.11121/ijocta.01.2018.00568Akgül, A., Inc, M., & Karatas, E. (2015). Reproducing kernel functions for difference equations. Discrete & Continuous Dynamical Systems - S, 8(6), 1055-1064. doi:10.3934/dcdss.2015.8.1055Akgül, A., Inc, M., Karatas, E., & Baleanu, D. (2015). Numerical solutions of fractional differential equations of Lane-Emden type by an accurate technique. Advances in Difference Equations, 2015(1). doi:10.1186/s13662-015-0558-8Aronszajn, N. (1950). Theory of reproducing kernels. Transactions of the American Mathematical Society, 68(3), 337-337. doi:10.1090/s0002-9947-1950-0051437-7Bergman, S. (1950). The Kernel Function and Conformal Mapping. Mathematical Surveys and Monographs. doi:10.1090/surv/005Inc, M., & Akgül, A. (2014). Approximate solutions for MHD squeezing fluid flow by a novel method. Boundary Value Problems, 2014(1). doi:10.1186/1687-2770-2014-18Inc, M., Akgül, A., & Geng, F. (2014). Reproducing Kernel Hilbert Space Method for Solving Bratu’s Problem. Bulletin of the Malaysian Mathematical Sciences Society, 38(1), 271-287. doi:10.1007/s40840-014-0018-8Wang, Y., & Chao, L. (2008). Using reproducing kernel for solving a class of partial differential equation with variable-coefficients. Applied Mathematics and Mechanics, 29(1), 129-137. doi:10.1007/s10483-008-0115-yWu, B. Y., & Li, X. Y. (2011). A new algorithm for a class of linear nonlocal boundary value problems based on the reproducing kernel method. Applied Mathematics Letters, 24(2), 156-159. doi:10.1016/j.aml.2010.08.036Yao, H., & Lin, Y. (2009). Solving singular boundary-value problems of higher even-order. Journal of Computational and Applied Mathematics, 223(2), 703-713. doi:10.1016/j.cam.2008.02.01

    REPRODUCING KERNEL METHOD FOR SOLVING FUZZY INITIAL VALUE PROBLEMS

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    In this thesis, numerical solution of the fuzzy initial value problem will be investigated based on the reproducing kernel method. Problems of this type are either difficult to solve or impossible, in some cases, since they will produce a complicated optimized problem. To overcome this challenge, reproducing kernel method will be modified to solve this type of problems. Theoretical and numerical results will be presented to show the efficiency of the proposed method

    Fractional Bernstein operational matrices for solving integro-differential equations involved by Caputo fractional derivative

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    The present work is devoted to developing two numerical techniques based on fractional Bernstein polynomials, namely fractional Bernstein operational matrix method, to numerically solving a class of fractional integro-differential equations (FIDEs). The first scheme is introduced based on the idea of operational matrices generated using integration, whereas the second one is based on operational matrices of differentiation using the collocation technique. We apply the Riemann–Liouville and fractional derivative in Caputo’s sense on Bernstein polynomials, to obtain the approximate solutions of the proposed FIDEs. We also provide the residual correction procedure for both methods to estimate the absolute errors. Some results of the perturbation and stability analysis of the methods are theoretically and practically presented. We demonstrate the applicability and accuracy of the proposed schemes by a series of numerical examples. The numerical simulation exactly meets the exact solution and reaches almost zero absolute error whenever the exact solution is a polynomial. We compare the algorithms with some known analytic and semi-analytic methods. As a result, our algorithm based on the Bernstein series solution methods yield better results and show outstanding and optimal performance with high accuracy orders compared with those obtained from the optimal homotopy asymptotic method, standard and perturbed least squares method, CAS and Legendre wavelets method, and fractional Euler wavelet method

    Error Analyses for Nyström Methods for Solving Fredholm Integral and Integro-Differential Equations

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    This thesis concerns the development and implementation of novel error analyses for ubiquitous Nyström-type methods used in approximating the solution in 1-D of both Fredholm integral- and integro-differential equations of the second-kind, (FIEs) and (FIDEs). The distinctive contribution of the present work is that it offers a new systematic procedure for predicting, to spectral accuracy, error bounds in the numerical solution of FIEs and FIDEs when the solution is, as in most practical applications, a priori unknown. The classic Legendre-based Nyström method is extended through Lagrange interpolation to admit solution of FIEs by collocation on any nodal distribution, in particular, those that are optimal for not only integration but also differentiation. This offers a coupled extension of optimal-error methods for FIEs into those for FIDEs. The so-called FIDE-Nyström method developed herein motivates yet another approach in which (demonstrably ill-conditioned) numerical differentiation is bypassed by reformulating FIDEs as hybrid Volterra-Fredholm integral equations (VFIEs). A novel approach is used to solve the resulting VFIEs that utilises Lagrange interpolation and Gaussian quadrature for the Volterra and Fredholm components respectively. All error bounds implemented for the above numerical methods are obtained from novel, often complex extensions of an established but hitherto-unimplemented theoretical Nyström-error framework. The bounds are computed using only the available computed numerical solution, making the methods of practical value in, e.g., engineering applications. For each method presented, the errors in the numerical solution converge (sometimes exponentially) to zero with N, the number of discrete collocation nodes; this rate of convergence is additionally confirmed via large-N asymptotic estimates. In many cases these bounds are spectrally accurate approximations of the true computed errors; in those cases that the bounds are not, the non-applicability of the theory can be predicted either a priori from the kernel or a posteriori from the numerical solution

    New Challenges Arising in Engineering Problems with Fractional and Integer Order

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    Mathematical models have been frequently studied in recent decades, in order to obtain the deeper properties of real-world problems. In particular, if these problems, such as finance, soliton theory and health problems, as well as problems arising in applied science and so on, affect humans from all over the world, studying such problems is inevitable. In this sense, the first step in understanding such problems is the mathematical forms. This comes from modeling events observed in various fields of science, such as physics, chemistry, mechanics, electricity, biology, economy, mathematical applications, and control theory. Moreover, research done involving fractional ordinary or partial differential equations and other relevant topics relating to integer order have attracted the attention of experts from all over the world. Various methods have been presented and developed to solve such models numerically and analytically. Extracted results are generally in the form of numerical solutions, analytical solutions, approximate solutions and periodic properties. With the help of newly developed computational systems, experts have investigated and modeled such problems. Moreover, their graphical simulations have also been presented in the literature. Their graphical simulations, such as 2D, 3D and contour figures, have also been investigated to obtain more and deeper properties of the real world problem

    An attractive numerical algorithm for solving nonlinear Caputo-Fabrizio fractional Abel differential equation in a Hilbert space

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    Our aim in this paper is presenting an attractive numerical approach giving an accurate solution to the nonlinear fractional Abel differential equation based on a reproducing kernel algorithm with model endowed with a Caputo-Fabrizio fractional derivative. By means of such an approach, we utilize the Gram-Schmidt orthogonalization process to create an orthonormal set of bases that leads to an appropriate solution in the Hilbert space H-2[a, b]. We investigate and discuss stability and convergence of the proposed method. The n-term series solution converges uniformly to the analytic solution. We present several numerical examples of potential interests to illustrate the reliability, efficacy, and performance of the method under the influence of the Caputo-Fabrizio derivative. The gained results have shown superiority of the reproducing kernel algorithm and its infinite accuracy with a least time and efforts in solving the fractional Abel-type model. Therefore, in this direction, the proposed algorithm is an alternative and systematic tool for analyzing the behavior of many nonlinear temporal fractional differential equations emerging in the fields of engineering, physics, and sciences

    Complex Variable Meshless Manifold Method for Elastic Dynamic Problems

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    Combining the finite covering technical and complex variable moving least square, the complex variable meshless manifold method can handle the discontinuous problem effectively. In this paper, the complex variable meshless method is applied to solve the problem of elastic dynamics, the complex variable meshless manifold method for dynamics is established, and the corresponding formula is derived. The numerical example shows that the numerical solutions are in good agreement with the analytical solution. The CVMMM for elastic dynamics and the discrete forms are correct and feasible. Compared with the traditional meshless manifold method, the CVMMM has higher accuracy in the same distribution of nodes

    An elegant operational matrix based on harmonic numbers: Effective solutions for linear and nonlinear fourth-order two point boundary value problems

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    This paper analyzes the solution of fourth-order linear and nonlinear two point boundary value problems. The suggested method is quite innovative and it is completely different from all previous methods used for solving such kind of boundary value problems. The method is based on employing an elegant operational matrix of derivatives expressed in terms of the well-known harmonic numbers. Two algorithms are presented and implemented for obtaining new approximate solutions of linear and nonlinear fourth-order boundary value problems. The two algorithms rely on employing the new introduced operational matrix for reducing the differential equations with their boundary conditions to systems of linear or nonlinear algebraic equations which can be efficiently solved by suitable solvers. For this purpose, the two spectral methods namely, Petrov-Galerkin and collocation methods are applied. Some illustrative examples are considered aiming to ascertain the wide applicability, validity, and efficiency of the two proposed algorithms. The obtained numerical results are satisfactory and the approximate solutions are very close to the analytical solutions and they are more accurate than those obtained by some other existing techniques in literature
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