The multi-term time-fractional order diffusion-wave equation (MT-TFDWE) is an important mathematical model for processes exhibiting anomalous diffusion and wave propagation with memory effects. This article develops a robust numerical technique based on the Chebyshev collocation method (CCM) coupled with the Laplace transform (LT) to solve the time-fractional diffusion-wave equation. The CCM is utilized to discretize the spatial domain, which ensures remarkable accuracy and excellent efficiency in capturing the variations of spatial solutions. The LT is used to handle the time-fractional derivative, which converts the problem into an algebraic equation in a simple form. However, while using the LT, the main difficulty arises in calculating its inverse. In many situations, the analytical inversion of LT becomes a cumbersome job. Therefore, the numerical techniques are then used to obtain the time domain solution from the frequency domain solution. Various numerical inverse Laplace transform methods (NILTMs) have been developed by the researchers. In this work, we use the contour integration method (CIM), which is capable of handling complex inversion tasks efficiently. This hybrid technique provides a powerful tool for the numerical solution of the time-fractional diffusion-wave equation. The accuracy and efficiency of the proposed technique are validated through four test problems.
Citation: Farman Ali Shah, Kamran, Zareen A Khan, Fatima Azmi, Nabil Mlaiki. A hybrid collocation method for the approximation of 2D time fractional diffusion-wave equation[J]. AIMS Mathematics, 2024, 9(10): 27122-27149. doi: 10.3934/math.20241319
The multi-term time-fractional order diffusion-wave equation (MT-TFDWE) is an important mathematical model for processes exhibiting anomalous diffusion and wave propagation with memory effects. This article develops a robust numerical technique based on the Chebyshev collocation method (CCM) coupled with the Laplace transform (LT) to solve the time-fractional diffusion-wave equation. The CCM is utilized to discretize the spatial domain, which ensures remarkable accuracy and excellent efficiency in capturing the variations of spatial solutions. The LT is used to handle the time-fractional derivative, which converts the problem into an algebraic equation in a simple form. However, while using the LT, the main difficulty arises in calculating its inverse. In many situations, the analytical inversion of LT becomes a cumbersome job. Therefore, the numerical techniques are then used to obtain the time domain solution from the frequency domain solution. Various numerical inverse Laplace transform methods (NILTMs) have been developed by the researchers. In this work, we use the contour integration method (CIM), which is capable of handling complex inversion tasks efficiently. This hybrid technique provides a powerful tool for the numerical solution of the time-fractional diffusion-wave equation. The accuracy and efficiency of the proposed technique are validated through four test problems.
[1] | K. Shah, H. Naz, M. Sarwar, T. Abdeljawad, On spectral numerical method for variable-order partial differential equations, AIMS Math., 7 (2022). 10422–10438. https://doi.org/10.3934/math.2022581 |
[2] | K. Shah, T. Abdeljawad, M. B. Jeelani, M. A. Alqudah, Spectral analysis of variable-order multi-terms fractional differential equations, Open Phys., 21 (2023), 20230136. https://doi.org/10.1515/phys-2023-0136 doi: 10.1515/phys-2023-0136 |
[3] | F. A. Shah, Kamran, K. Shah, T. Abdeljawad, Numerical modelling of advection diffusion equation using Chebyshev spectral collocation method and Laplace transform, Results Appl. Math., 21 (2022), 100420. https://doi.org/10.1016/j.rinam.2023.100420 doi: 10.1016/j.rinam.2023.100420 |
[4] | R. L. McCrory, S. A. Orszag, Spectral methods for multi-dimensional diffusion problems, J. Comput. Phys., 37 (1980), 93–112. https://doi.org/10.1016/0021-9991(80)90006-6 doi: 10.1016/0021-9991(80)90006-6 |
[5] | W. Bourke, Spectral methods in global climate and weather prediction models, in Physically Based Modelling and Simulation of Climate and Climatic Change, Part 1, Springer, Dordrecht, 1988. |
[6] | P. Maraner, E. Onofri, G. P. Tecchioli, Spectral methods in computational quantum mechanics, J. Comput. Appl. Math., 37 (1991), 209–219. https://doi.org/10.1016/0377-0427(91)90119-5 doi: 10.1016/0377-0427(91)90119-5 |
[7] | L. N. Trefethen, Spectral methods in MATLAB, SIAM, Philadelphia, 2000. |
[8] | A. Bueno-Orovio, V. M. Perez-Garcia, F. H. Fenton, Spectral methods for partial differential equations in irregular domains: the spectral smoothed boundary method, SIAM J. Sci. Comput., 28 (2006), 886–900. https://doi.org/10.1137/040607575 doi: 10.1137/040607575 |
[9] | I. Ahmad, H. Ahmad, P. Thounthong, Y. M. Chu, C. Cesarano, Solution of multi-term time-fractional PDE models arising in mathematical biology and physics by local meshless method, Symmetry, 12 (2020), 11–95. https://doi.org/10.3390/sym12071195 doi: 10.3390/sym12071195 |
[10] | F. Mainardi, Fractional diffusive waves in viscoelastic solids, Nonlinear Waves Solids, 137 (1995), 93–97. https://doi.org/10.1142/S0218396X01000826 doi: 10.1142/S0218396X01000826 |
[11] | L. Qiu, X. Ma, Q. H. Qin, A novel meshfree method based on spatio-temporal homogenization functions for one-dimensional fourth-order fractional diffusion-wave equations, Appl. Math. Lett., 142 (2023), 108657. https://doi.org/10.1016/j.aml.2023.108657 doi: 10.1016/j.aml.2023.108657 |
[12] | V. Srivastava, K. N. Rai, A multi-term fractional diffusion equation for oxygen delivery through a capillary to tissues, Math. Comput. Modell., 51 (2010), 616–624. https://doi.org/10.1016/j.mcm.2009.11.002 doi: 10.1016/j.mcm.2009.11.002 |
[13] | I. Ahmad, I. Ali, R. Jan, S. A. Idris, M. Mousa, Solutions of a three-dimensional multiterm fractional anomalous solute transport model for contamination in groundwater, Plos one, 18 (2023), e0294348. https://doi.org/10.1371/journal.pone.0294348 doi: 10.1371/journal.pone.0294348 |
[14] | L. Qiu, M. Zhang, Q. H. Qin, Homogenization function method for time-fractional inverse heat conduction problem in 3D functionally graded materials, Appl. Math. Lett., 122 (2021), 107478. https://doi.org/10.1016/j.aml.2021.107478 doi: 10.1016/j.aml.2021.107478 |
[15] | Podlubny, Fractional Differential Equations, Academic Press, San Diego, 1999. |
[16] | H. Jiang, F. Liu, I. Turner, K. Burrage, Analytical solutions for the multi-term time-fractional diffusion-wave/diffusion equations in a finite domain, Comput. Math. Appl., 64 (2012), 3377–3388. https://doi.org/10.1016/j.camwa.2012.02.042 doi: 10.1016/j.camwa.2012.02.042 |
[17] | X. J. Liu, J. Z. Wang, X. M. Wang, Y. H. Zhou, Exact solutions of multi-term fractional diffusion-wave equations with Robin type boundary conditions, Appl. Math. Mech., 35 (2014), 49–62. https://doi.org/10.1007/s10483-014-1771-6 doi: 10.1007/s10483-014-1771-6 |
[18] | Z. J. Fu, L. W. Yang, H. Q. Zhu, W. Z. Xu, A semi-analytical collocation Trefftz scheme for solving multi-term time fractional diffusion-wave equations, Eng. Anal. Bound. Elem., 98 (2019), 13–146. https://doi.org/10.1016/j.enganabound.2018.09.017 doi: 10.1016/j.enganabound.2018.09.017 |
[19] | Z. Z. Sun, C. C. Ji, R. Du, A new analytical technique of the L-type difference schemes for time fractional mixed sub-diffusion and diffusion-wave equations, Appl. Math. Lett., 102 (2020), 106–115. https://doi.org/10.1016/j.aml.2019.106115 doi: 10.1016/j.aml.2019.106115 |
[20] | V. Daftardar-Gejji, S. Bhalekar, Solving multi-term linear and non-linear diffusion-wave equations of fractional order by Adomian decomposition method, Appl. Math. Comput., 202 (2008), 113–120. https://doi.org/10.1016/j.amc.2008.01.027 doi: 10.1016/j.amc.2008.01.027 |
[21] | R. Salehi, A meshless point collocation method for 2-D multi-term time fractional diffusion-wave equation, Numer. Algorithm, 74 (2017), 1145–1168. DOI 10.1007/s11075-016-0190-z doi: 10.1007/s11075-016-0190-z |
[22] | F. Soltani Sarvestani, M. H. Heydari, A. Niknam, Z. Avazzadeh, A wavelet approach for the multi-term time fractional diffusion-wave equation, Internat. J. Comput. Math., 96 (2019), 640–661. https://doi.org/10.1080/00207160.2018.1458097 doi: 10.1080/00207160.2018.1458097 |
[23] | H. Jafari, A. Golbabai, S. Seifi, K. Sayevand, Homotopy analysis method for solving multiterm linear and nonlinear diffusion-wave equations of fractional order, Comput. Math. Appl., 59 (2010), 1337–1344. https://doi.org/10.1016/j.camwa.2009.06.020 doi: 10.1016/j.camwa.2009.06.020 |
[24] | Y. B. Wei, Y. M. Zhao, Z. G. Shi, F. L. Wang, Y. F. Tang, Spatial high accuracy analysis of FEM for two-dimensional multi-term time-fractional diffusion-wave equations, Acta Math. Appl. Sinica, Engl. Ser., 34 (2018), 828–841. https://10.1007/s10255-018-0795-1 doi: 10.1007/s10255-018-0795-1 |
[25] | X. Zhang, Y. Feng, Z. Luo, J. Liu, A spatial sixth-order numerical scheme for solving fractional partial differential equation, Appl. Math. Lett., 159 (2024), 109265. https://doi.org/10.1016/j.aml.2024.109265 doi: 10.1016/j.aml.2024.109265 |
[26] | M. A. Jafari, A. Aminataei, An algorithm for solving multi-term diffusion-wave equations of fractional order, Comput. Math. Appl., 62 (2011), 1091–1097. https://doi.org/10.1016/j.camwa.2011.03.066 doi: 10.1016/j.camwa.2011.03.066 |
[27] | M. Dehghan, M. Safarpoor, M. Abbaszadeh, Two high-order numerical algorithms for solving the multi-term time fractional diffusion-wave equations, J. Comput. Appl. Math., 290 (2015), 174–195. https://doi.org/10.1016/j.cam.2015.04.037 doi: 10.1016/j.cam.2015.04.037 |
[28] | H. Chen, S. Lü, W. Chen, A unified numerical scheme for the multi-term time fractional diffusion and diffusion-wave equations with variable coefficients, J. Comput. Appl. Math., 330 (2018), 380–397. https://doi.org/10.1016/j.cam.2017.09.011 doi: 10.1016/j.cam.2017.09.011 |
[29] | F. Liu, M. M. Meerschaert, R. J. McGough, P. Zhuang, Q. Liu, Numerical methods for solving the multi-term time-fractional wave-diffusion equation, Fract. Calc. Appl. Anal., 16 (2013), 9–25. doi:10.2478/s13540-013-0002-2 doi: 10.2478/s13540-013-0002-2 |
[30] | M. Li, C. Huang, W. Ming, Mixed finite-element method for multi-term time-fractional diffusion and diffusion-wave equations, Comput. Appl. Math., 37 (2018), 2309–2334. https://doi.org/10.1007/s40314-017-0447-8 doi: 10.1007/s40314-017-0447-8 |
[31] | J. Ren, Z. Z. Sun, Efficient numerical solution of the multi-term time fractional diffusion-wave equation, East Asian J. Appl. Math., 5 (2015), 1–28. https://doi.org/10.4208/eajam.080714.031114a doi: 10.4208/eajam.080714.031114a |
[32] | M. Saffarian, A. Mohebbi, The Galerkin spectral element method for the solution of two-dimensional multiterm time fractional diffusion-wave equation, Math. Methods Appl. Sci., 44 (2021), 2842–2858. https://doi.org/10.1002/mma.6049 doi: 10.1002/mma.6049 |
[33] | B. Jin, R. Lazarov, Y. Liu, Z. Zhou, The Galerkin finite element method for a multi-term time-fractional diffusion equation, J. Comput. Phys., 281 (2015), 825–843. https://doi.org/10.1016/j.jcp.2014.10.051 doi: 10.1016/j.jcp.2014.10.051 |
[34] | H. Zhang, F. Liu, X. Jiang, I. Turner, Spectral method for the two-dimensional time distributed-order diffusion-wave equation on a semi-infinite domain, J. Comput. Appl. Math., 399 (2022), 113712. https://doi.org/10.1016/j.cam.2021.113712 doi: 10.1016/j.cam.2021.113712 |
[35] | J. Rashidinia, E. Mohmedi, Approximate solution of the multi-term time fractional diffusion and diffusion-wave equations, Comput. Appl. Math., 39 (2020), 1–25. https://doi.org/10.1007/s40314-020-01241-4 doi: 10.1007/s40314-020-01241-4 |
[36] | M. A. Zaky, J. T. Machado, Multi-dimensional spectral tau methods for distributed-order fractional diffusion equations, Comput. Math. Appl., 79 (2020), 476–488. https://doi.org/10.1016/j.camwa.2019.07.008 doi: 10.1016/j.camwa.2019.07.008 |
[37] | S. S. Bhavikatti, Finite element analysis, New Age International, New Delhi, 2005. |
[38] | Z. Bi, Finite element analysis applications: a systematic and practical approach, Academic Press, Cambridge, Massachusetts, 2017. |
[39] | E. A. Sudicky, R. G. McLaren, The Laplace transform Galerkin technique for large-scale simulation of mass transport in discretely fractured porous formations, Water Resour. Res., 28 (1992), 499–514. https://doi.org/10.1029/91WR02560 doi: 10.1029/91WR02560 |
[40] | S. F. A. Kamran, W. H. F. Aly, H. Aksoy, F. M. Alotaibi, I. Mahariq, Numerical inverse Laplace transform methods for advection-diffusion problems, Symmetry, 14 (2022), 2544. https://doi.org/10.3390/sym14122544 doi: 10.3390/sym14122544 |
[41] | Z. J. Fu, W. Chen, H. T. Yang, Boundary particle method for Laplace transformed time fractional diffusion equations, J. Comput. Phys., 235 (2013), 52–66. https://doi.org/10.1016/j.jcp.2012.10.018 doi: 10.1016/j.jcp.2012.10.018 |
[42] | K. L. Kuhlman, Review of inverse Laplace transform algorithms for Laplace-space numerical approaches, Numer. Algorithms, 63 (2013), 339–355. DOI 10.1007/s11075-012-9625-3 doi: 10.1007/s11075-012-9625-3 |
[43] | W. Wang, Z. Dai, J. Li, L. Zhou, A hybrid Laplace transform finite analytic method for solving transport problems with large Peclet and Courant numbers, Comput. Geosci., 49 (2012), 182–189. https://doi.org/10.1016/j.cageo.2012.05.020 doi: 10.1016/j.cageo.2012.05.020 |
[44] | G. J. Moridis, D. L. Reddell, The Laplace transform finite difference method for simulation of flow through porous media, Water Resour. Res., 27 (1991), 1873–1884. https://doi.org/10.1029/91WR01190 doi: 10.1029/91WR01190 |
[45] | C. Canuto, M. Y. Hussaini, A. Quarteroni, T. A. Zang, Spectral methods: evolution to complex geometries and applications to fluid dynamics, Springer, Berlin, Heidelberg, 2007. |
[46] | K. S. Crump, Numerical inversion of Laplace transforms using a Fourier series approximation, J. ACM, 23 (1976), 89–96. https://dl.acm.org/doi/pdf/10.1145/321921.321931 doi: 10.1145/321921.321931 |
[47] | F. R. De Hoog, J. H. Knight, A. N. Stokes, An improved method for numerical inversion of Laplace transforms, SIAM J. Sci. Stat. Comput., 3 (1982), 357–366. https://doi.org/10.1137/0903022 doi: 10.1137/0903022 |
[48] | H. Stehfest, Algorithm 368: Numerical inversion of Laplace transforms [D5], Commun. ACM, 13 (1970), 47–49. https://doi.org/10.1145/361953.361969 doi: 10.1145/361953.361969 |
[49] | A. Talbot, The accurate numerical inversion of Laplace transforms, IMA J. Appl. Math., 23 (1979), 97–120. https://doi.org/10.1093/imamat/23.1.97 doi: 10.1093/imamat/23.1.97 |
[50] | J. Weideman, L. N. Trefethen, Parabolic and hyperbolic contours for computing the Bromwich integral, Math. Comput., 76 (2007), 1341–1356. https://doi.org/10.1090/S0025-5718-07-01945-X doi: 10.1090/S0025-5718-07-01945-X |
[51] | W. T. Weeks, Numerical inversion of Laplace transforms using Laguerre functions, J. ACM, 13 (1966), 419–429. https://doi.org/10.1145/321341.321351 doi: 10.1145/321341.321351 |
[52] | W. McLean, V. Thomee, Numerical solution via Laplace transforms of a fractional order evolution equation, J. Integral Equations Appl. 22 (2010), 57–94. https://doi.org/10.1216/JIE-2010-22-1-57 |
[53] | P. Verma, M. Kumar, New existence, uniqueness results for multi-dimensional multi-term Caputo time-fractional mixed sub-diffusion and diffusion-wave equation on convex domains, J. Appl. Anal. Comput., 11 (2021), 1455–1480. https://doi.org/10.11948/20200217 doi: 10.11948/20200217 |
[54] | J. V. D. C. Sousa, E. C. de Oliveira, On the stability of a hyperbolic fractional partial differential equation, Differ. Equ. Dynam. Systems, 31 (2023), 31–52. https://doi.org/10.1007/s12591-019-00499-3 doi: 10.1007/s12591-019-00499-3 |
[55] | D. Funaro, Polynomial approximation of differential equations, Springer Verlag, New York, 2008. |
[56] | B. D. Welfert, Generation of pseudospectral differentiation matrices I, SIAM J. Numer. Anal., 34 (1997), 1640–1657. https://www.jstor.org/stable/2952067 |
[57] | A. Shokri, S. Mirzaei, A pseudo-spectral based method for time-fractional advection-diffusion equation, Comput. Methods Differ. Equ., 8 (2020), 454–467. https://doi.org/10.22034/cmde.2020.29307.1414 doi: 10.22034/cmde.2020.29307.1414 |
[58] | R. Baltensperger, M. R. Trummer, Spectral differencing with a twist, SIAM J. Sci. Comput., 24 (2003), 1465–1487. https://doi.org/10.1137/S1064827501388182 doi: 10.1137/S1064827501388182 |
[59] | S. Börm, L. Grasedyck, W. Hackbusch, Introduction to hierarchical matrices with applications, Eng. Anal. Bound. Elements, 27 (2003), 405–422. https://doi.org/10.1016/S0955-7997(02)00152-2 doi: 10.1016/S0955-7997(02)00152-2 |