Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-10T15:14:47.021Z Has data issue: false hasContentIssue false

Analysis of Mathematics and Numerical Pattern Formation in Superdiffusive Fractional Multicomponent System

Published online by Cambridge University Press:  28 November 2017

Kolade M. Owolabi*
Affiliation:
Institute for Groundwater Studies, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9300, South Africa
Abdon Atangana*
Affiliation:
Institute for Groundwater Studies, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9300, South Africa
*
*Corresponding author. Emails:mkowolax@yahoo.com (K. M. Owolabi), abdonatangana@yahoo.fr (A. Atangana)
*Corresponding author. Emails:mkowolax@yahoo.com (K. M. Owolabi), abdonatangana@yahoo.fr (A. Atangana)
Get access

Abstract

In this work, we examine the mathematical analysis and numerical simulation of pattern formation in a subdiffusive multicomponents fractional-reaction-diffusion system that models the spatial interrelationship between two preys and predator species. The major result is centered on the analysis of the system for linear stability. Analysis of the main model reflects that the dynamical system is locally and globally asymptotically stable. We propose some useful theorems based on the existence and permanence of the species to validate our theoretical findings. Reliable and efficient methods in space and time are formulated to handle any space fractional reaction-diffusion system. We numerically present the complexity of the dynamics that are theoretically discussed. The simulation results in one, two and three dimensions show some amazing scenarios.

Type
Research Article
Copyright
Copyright © Global-Science Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Atangana, A., On the stability and convergence of the time-fractional variable order telegraph equation, J. Comput. Phys., 293 (2015), pp. 104114.CrossRefGoogle Scholar
[2] Atangana, A., On the new fractional derivative and application to Fisher's reaction-diffusion, Appl. Math. Comput., 273 (2016) 948956.Google Scholar
[3] Atangana, A. and Baleanu, D., New fractional derivatives with nonlocal and non-singular kernel: Theory and application to heat transfer model, Thermal Science, 20 (2016), pp. 763769.CrossRefGoogle Scholar
[4] Atangana, A. and Koca, I., Chaos in a simple nonlinear system with Atangana-Baleanu derivatives with fractional order, Chaos, Solitons & Fractals, 89 (2016), pp. 447454.CrossRefGoogle Scholar
[5] Arnoldi, W., The principle of minimized iteration in the solution of the matrix eigenvalue problem, Quarterly Appl. Math., 9 (1951), pp. 1729.CrossRefGoogle Scholar
[6] Bainov, D. D. and Simeonov, P. C., Impulsive Differential Equations: Asymptotic Properties of the Solutions, World Scientific, Singapore, 1993.Google Scholar
[7] Baleanu, D., Golmankhaneh, A., Nigmatullin, R. and Golmankhaneh, A., Fractional newtonian mechanics, Open Phys., 8 (2010), pp. 120125.CrossRefGoogle Scholar
[8] Bhrawy, A. H., Zaky, M. A., Baleanu, D. and Abdelkawy, M. A., A novel spectral approximation for the two-dimensional fractional sub-diffusion problems, Rom. J. Phys., 60 (2015), pp. 344359.Google Scholar
[9] Bhrawy, A. H., An efficient Jacobi pseudospectral approximation for nonlinear complex generalized Zakharov system, Appl. Math. Comput., 247 (2014), pp. 3046.Google Scholar
[10] Bhrawy, A. H., Doha, E. H., Baleanu, D. and Ezz-Eldein, S. S., A spectral tau algorithm based on Jacobi operational matrix for numerical solution of time fractional diffusion-wave equations, J. Comput. Phys., 293 (2015), pp. 142156.CrossRefGoogle Scholar
[11] Bhrawy, A. H., A Jacobi spectral collocation method for solving multi-dimensional nonlinear fractional sub-diffusion equations, Numer. Algorithms, 17 (2016), pp. 91113. DOI: 10.1007/s11075-015-0087-2CrossRefGoogle Scholar
[12] Bhrawy, A. H., A new spectral algorithm for a time-space fractional partial differential equations with subdiffusion and superdiffusion, Proceedings of the Romanian Academy A, 17 (2016), pp. 3946.Google Scholar
[13] Boyd, J. P., Chebyshev and Fourier Spectral Methods, Dover, Mineola, New York, 2001.Google Scholar
[14] Bueno-Orovio, A., Kay, D. and Burrage, K., Fourier spectral methods for fractional-in-space reaction-diffusion equations, BIT Numer. Math., 54 (2014), pp. 937954.CrossRefGoogle Scholar
[15] Cantrell, R. S. and Cosner, C., Permanence in ecological systems with spatial heterogeneity, Proc. Roy. Soc. Edinburgh, 123A (1993), pp. 533559.CrossRefGoogle Scholar
[16] Chang, Y., Feng, W., Freeze, M. and Lu, X., Permanence and coexistence in a diffusive complex ratio-dependent food chain, Int. J. Dyn. Control Systems, DOI:10.1007/s40435-014-0131-4 (2014).CrossRefGoogle Scholar
[17] Cox, S. M. and Matthews, P. C., Exponential time differencing for stiff systems, J. Comput. Phys., 176 (2002), pp. 430455.CrossRefGoogle Scholar
[18] Dancer, E. N., The existence and Uniqueness of positive solutions of competing species equations with diffusion, Trans. Amer. Math. Soc., 326 (1991), pp. 829859.CrossRefGoogle Scholar
[19] Doha, E. H., Bhrawy, A. H., Baleanu, D. and Hafez, R. M., A new Jacobi rational-Gauss collocation method for numerical solution of generalized pantograph equations, Appl. Numer. Math., 77 (2014), pp. 4354.CrossRefGoogle Scholar
[20] Du, Q. and Zhu, W., Analysis and applications of the exponential time differencing schemes and their contour integration modifications, BIT Numer. Math., 45 (2005), pp. 307328.CrossRefGoogle Scholar
[21] Feng, W., Permanence effect in a three-species food chain model, Appl. Anal., 54 (1994), pp. 195209.Google Scholar
[22] Feng, W., Pao, C. V. and Lu, X., Global attractors of reaction-diffusion system modeling food chain populations with delays, Commun. Pure Appl. Anal., 10, pp. 14631478.CrossRefGoogle Scholar
[23] Feng, W., Cowen, M. T. and Lu, X., Coexistence and asymptotic stability in age-structured predator-prey models, Math. Biosci. Eng., 11 (2014), pp. 823839.CrossRefGoogle Scholar
[24] Fornberg, B., A practical Guide to Pseudospectral Methods, Cambridge University Press, Cambridge, 1998.Google Scholar
[25] Garvie, M., Finite-difference schemes for reaction-diffusion equations modeling predator-pray interactions in MATLAB, Bull. Math. Bio., 69 (2007), pp. 931956.Google Scholar
[26] Gómez-Aguilar, J. F., López-López, M. G., Alvarado-Martínez, V. M., Reyes-Reyes, J. and Adam-Medina, M., Modeling diffusive transport with a fractional derivative without singular kernel, Phys. A Stat. Mech. Appl., 447 (2016), pp. 467481.CrossRefGoogle Scholar
[27] Gómez-Aguilar, J. F., Torres, L., Yépez-Martínez, H., Baleanu, D., Reyes, J. M. and Sosa, I. O., Fractional Linard type model of a pipeline within the fractional derivative without singular kernel, Adv. Difference Equations, 2016(1) (2016), pp. 113.CrossRefGoogle Scholar
[28] Haque, M., Ratio-dependent predator-prey models of interacting populations, Bull. Math. Bio., 71 (2009), pp. 430452.CrossRefGoogle ScholarPubMed
[29] Henry, B. I. and Wearne, S. L., Fractional reaction-diffusion, Phys. A Stat. Mech. Appl., 276 (2000), pp. 448455.CrossRefGoogle Scholar
[30] Hochbruck, M. and Ostermann, A., Exponential integrators, Acta Numer., 19 (2010), pp. 209286.CrossRefGoogle Scholar
[31] Hochbruck, M. and Ostermann, A., Exponential multistep methods of Adams-type, BIT Numer. Math., 51 (2011), pp. 889908.CrossRefGoogle Scholar
[32] Holmes, W. R., An efficient, nonlinear stability analysis for detecting pattern formation in reaction diffusion systems, Bull. Math. Bio., 76 (2014), pp. 157183.CrossRefGoogle ScholarPubMed
[33] Holt, R. D., Predation, apparent competition, and the structure of prey communities, Theoretical Population Biology, 12 (1997), pp. 197229.CrossRefGoogle Scholar
[34] Jiao, J., Chen, L. and Li, L., Asymptotic behavior of solutions of second-order nonlinear impulsive differential equations, J. Math. Anal. Appl., 331 (2008), pp. 458463.CrossRefGoogle Scholar
[35] Kassam, A. and Trefethen, L. N., Fourth-order time-stepping for stiff PDEs, SIAM J. Sci. Comput., 26 (2005), pp. 12141233.CrossRefGoogle Scholar
[36] Lakshmikantham, V., Bainov, D. D. and Simeonov, P. C., Theory of Impulsive Differential Equations, World Scientific, Singapore, 1989.CrossRefGoogle Scholar
[37] Leung, A., Limiting behaviour for a prey-predator model with diffusion and crowding effects, J. Math. Bio., 6 (1978), pp. 8793.CrossRefGoogle Scholar
[38] Leung, A., Systems of Nonlinear Partial Differential Equations, Kluwer Publisher, Boston, 1989.CrossRefGoogle Scholar
[39] Morales-Delgado, V. F., Gómez-Aguilar, J. F., Yépez-Martínez, H., Baleanu, D., Escobar-Jimenez, R. F. and Olivares-Peregrino, V. H., Laplace homotopy analysis method for solving linear partial differential equations using a fractional derivative with and without kernel singular, Adv. Difference Equations, 2016 (1), (2016).CrossRefGoogle Scholar
[40] Morgado, M. L. and Rebelo, M., Numerical approximation of distributed order reaction-diffusion equations, J. Comput. Appl. Math., 275 (2015), pp. 216227.CrossRefGoogle Scholar
[41] Murray, J. D., Mathematical Biology II: Spatial Models and Biomedical Applications, Springer-Verlag, Berlin, 2003.CrossRefGoogle Scholar
[42] Owolabi, K. M. and Patidar, K. C., Higher-order time-stepping methods for time-dependent reaction-diffusion equations arising in biology, Appl. Math. Comput., 240 (2014), pp. 3050.Google Scholar
[43] Owolabi, K. M., Robust IMEX schemes for solving two-dimensional reaction-diffusion models, Int. J. Nonlinear Sci. Numer. Simulations, 16 (2015), pp. 271284.CrossRefGoogle Scholar
[44] Owolabi, K. M. and Patidar, K. C., Existence and permanence in a diffusive KiSS modelwith robust numerical simulations, Int. J. Differential Equations, (2015), 485860, doi:10.1155/2015/485860.CrossRefGoogle Scholar
[45] Owolabi, K. M. and Patidar, K. C., Numerical simulations of multicomponent ecological models with adaptive methods, Theoret. Bio. Medical Model., 13 (2016), 1. DOI 10.1186/s12976-016-0027-4.CrossRefGoogle ScholarPubMed
[46] Owolabi, K. M. and Atangana, A., Numerical solution of fractional-in-space nonlinear Schrodinger equation with the Riesz fractional derivative, The Euro. Phys. J. Plus, 131 (2016), 335. Doi:10.1140/epjp/i2016-16335-8.CrossRefGoogle Scholar
[47] Owolabi, K. M., Mathematical analysis and numerical simulation of patterns in fractional and classical reaction-diffusion systems, Chaos, Solitons and Fractals, 93 (2016), pp. 8998.CrossRefGoogle Scholar
[48] Owolabi, K. M., Robust and adaptive techniques for numerical simulation of nonlinear partial differential equations of fractional order, Commun. Nonlinear Sci. Numer. Simulations, 44 (2017), pp. 304317.CrossRefGoogle Scholar
[49] Pindza, E., Owolabi, K. M., Fourier spectral method for higher order space fractional reaction-diffusion equations, Commun. Nonlinear Sci. Numer. Simulation, 40 (2016), pp. 112128.CrossRefGoogle Scholar
[50] Saad, Y., Analysis of some Krylov susbspace approximations to the matrix exponential operator, SIAM J. Numer. Anal., 131 (1992), pp. 209228.CrossRefGoogle Scholar
[51] Satnoianu, R. A., Menzinger, M. and Maini, P. K., Turing istabilities in general systems, J. Math. Bio., 41 (2000), pp. 493512.CrossRefGoogle ScholarPubMed
[52] Sun, G., Zhang, G., Jin, Z. and Li, L., Predator cannibalisms can give rise to regular spatial patterns in a predator-prey system, Nonlinear Dyn., 58 (2009), pp. 7584.CrossRefGoogle Scholar
[53] Sun, S. and Chen, L., Permanence and complexity of the Eco-Epidemiological model with impulsive perturbation, Int. J. Biomath., 1 (2008), pp. 121132.CrossRefGoogle Scholar
[54] Trefethen, L. N., Spectral Methods in MATLAB, SIAM, Philadelphia, 2000.CrossRefGoogle Scholar
[55] Uchaikin, V. V., Fractional Derivatives for Physicists and Engineers, Springer, Berlin, 2013.CrossRefGoogle Scholar
[56] Volpert, V. and Petrovskii, S., Reaction-diffusion waves in biology, Phys. Life Reviews, 6 (2009), pp. 267310.CrossRefGoogle ScholarPubMed
[57] Wang, H. and Wang, W., The dynamical complexity of a Ivler-type prey-predator system with impulsive effect, Chaos Solitons & Fractals 38 (2008), pp. 11681176.CrossRefGoogle Scholar
[58] Wang, L., Chen, L. and Nieto, J. J., The dynamics of an epidemic model for pest control with impulsive effect, Nonlinear Analysis: Real World Applications, (2010), pp. 13741386.Google Scholar
[59] Weideman, J. A. C. and Reddy, S. C., A MATLAB differentiation matrix suite, ACM Trans. Math. Software, 26 (2001), pp. 465519.CrossRefGoogle Scholar
[60] Wu, G. C., Baleanu, D., Zeng, S. D. and Deng, Z. G., Discrete fractional diffusion equation, Nonlinear Dyn., 80 (2015), pp. 281286.CrossRefGoogle Scholar
[61] Yu, H., Zhong, S. and Ye, M., Dynamic analysis of an ecological model with impulsive control strategy and distributed time delay, Math. Comput. Simulation, 80 (2009), pp. 619632.CrossRefGoogle Scholar
[62] Yu, H., Zhong, S., Ye, M. and Chen, W., Mathematical and dynamic analysis of an ecological model with an impulsive control strategy and distributed time delay, Math. Comput. Model., 50 (2009), pp. 16211635.CrossRefGoogle Scholar
[63] Yu, H., Zhong, S. and Agarwal, R. P., Mathematical Analysis of an apparent competition community model with impulsive effect, Math. Comput. Model., 52 (2010), pp. 2536.CrossRefGoogle Scholar
[64] Yu, H., Zhong, S., Agarwal, R. P. and Xiong, L., Species permanence and dynamical behavior analysis of an impulsively controlled ecological system with distributed time delay, Comput. Math. Appl., 59 (2010), pp. 38243835.CrossRefGoogle Scholar