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A Meshfree Technique for Numerical Simulation of Reaction-Diffusion Systems in Developmental Biology

Published online by Cambridge University Press:  11 July 2017

Zahra Jannesari*
Affiliation:
Department of Mathematical Sciences, Isfahan University of Technology, Isfahan, 84156-83111, Iran
Mehdi Tatari*
Affiliation:
Department of Mathematical Sciences, Isfahan University of Technology, Isfahan, 84156-83111, Iran Institute for Research in Fundamental Sciences (IPM), P.O. Box: 19395-5746, Tehran, Iran
*
*Corresponding author. Email:z.jannesari@math.iut.ac.ir (Z. Jannesari), mtatari@cc.iut.ac.ir (M. Tatari)
*Corresponding author. Email:z.jannesari@math.iut.ac.ir (Z. Jannesari), mtatari@cc.iut.ac.ir (M. Tatari)
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Abstract

In this work, element free Galerkin (EFG) method is posed for solving nonlinear, reaction-diffusion systems which are often employed in mathematical modeling in developmental biology. A predicator-corrector scheme is applied, to avoid directly solving of coupled nonlinear systems. The EFG method employs the moving least squares (MLS) approximation to construct shape functions. This method uses only a set of nodal points and a geometrical description of the body to discretize the governing equation. No mesh in the classical sense is needed. However a background mesh is used for integration purpose. Numerical solutions for two cases of interest, the Schnakenberg model and the Gierer-Meinhardt model, in various regions is presented to demonstrate the effects of various domain geometries on the resulting biological patterns.

Type
Research Article
Copyright
Copyright © Global-Science Press 2017 

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References

[1] Atluri, S. N. and Zhu, T., A modified collocation method and a penalty formulation for enforcing the essential boundary conditions in the element free Galerkin method, Comput. Mech., 21 (1998), pp. 211222.Google Scholar
[2] Atluri, S. N. and Zhu, T., A new meshless local petrov-Galerkin (MLPG) approach in computational mechanics, Comput. Mech. 22 (1998), pp. 117127.Google Scholar
[3] Atluri, S. N. and Shen, S., The Meshless Local Petrov-Galerkin (MLPG) Method, Tech Science Press, 2002.Google Scholar
[4] Barrio, S. R., Varea, C., Aragon, J. and Maini, P., A two-dimensional numerical study of spatial pattern formation in interacting systems, Bull. Math. Biol., 61 (1999), pp. 483505.Google Scholar
[5] Baurmanna, M., Gross, T. and Feudel, U., Instabilities in spatially extended predator-prey systems: spatio-temporal patterns in the neighborhood of Turing-Hopf bifurcations, J. Theor. Biol., 245 (2007), pp. 220229.Google Scholar
[6] Belytschko, T., Lu, Y. and Gu, L., Element free Galerkin methods, Int. J. Num. Meth. Eng., 37 (1994), pp. 229256.Google Scholar
[7] Chaplain, M., Ganesh, A. and Graham, I., Spatio-temporal pattern formation on spherical surfaces: numerical simulation and application to solid tumor growth, J. Math. Biol., 42 (2001), pp. 387423.Google Scholar
[8] Crampin, E., Gaffney, E. and Maini, P., Reaction and diffusion on growing domains: Scenarios for robust pattern formation, Bull. Math. Biol., 61 (1999), pp. 10931120.CrossRefGoogle ScholarPubMed
[9] Dolbow, J. and Belytschko, T., Numerical integration of the Galerkin weak form in meshfree methods, Comput. Mech., 23 (1999), pp. 219230.Google Scholar
[10] Dolbow, J. and Belytschko, T., An introduction to programming the meshless element free Galerkin method, Comput. Meth. Eng., 5(3) (1998), pp. 207241.Google Scholar
[11] Duarte, C. A. and Oden, J. T., An hp adaptive method using clouds, Comput. Methods Appl. Mech. Eng., 139 (1996), pp. 237262.Google Scholar
[12] Ferreira, S., Martins, M. and Vilela, M., Reaction-diffusion model for the growth of avascular tumor, Phys. Rev., 65(2) (2002), pp. 14671476.Google ScholarPubMed
[13] Frederik, H., Maini, P., Madzvamuse, A., Wathen, A. and Sekimura, T., Pigmentation pattern formation in butterflies: experiments and models, C. R. Biol., 326 (2003), pp. 717727.Google Scholar
[14] García-Aznar, J., Kuiper, J., Gómez-Benito, M., Doblaré, M. and Richardson, J., Computational simulation of fracture healing: influence of interfragmentary movement on the callus growth, J. Biomech., 40 (2007), pp. 14671476.Google Scholar
[15] Garzón-Alvarado, D. A., Galeano, C. H. and Mantilla, J. M., Turing pattern formation for reaction-convection-diffusion systems in fixed domains submitted to toroidal velocity fields, Appl. Math. Model., 35 (2011), pp. 49134925.Google Scholar
[16] Gierer, A. and Meinhardt, H., A theory of biological pattern formation, Kybernetik, 12 (1972), pp. 3039.Google Scholar
[17] Gockenbach, M. S., Understanding and Implementing the Finite Element Method, SIAM, 2006.Google Scholar
[18] Hundsdorfer, W. and Verwer, J., Numerical Solution of Time-Dependent Advection-Diffusion-Reaction Equations, Springer, Berlin, 2003.Google Scholar
[19] Kassam, A. and Trefethen, L., Solving reaction-diffusion equations 10 times faster, Oxford University: Numerical Analysis Group Research, Report 16, 2003.Google Scholar
[20] Kondo, S. and Asai, R., A reaction-diffusion wave on the skin of the marine anglefish Pomacanthus, Nature, 376 (1995), pp. 765768.Google Scholar
[21] Lancaster, P. and Salkauskas, K., Surface generated by moving least squares methods, Math. Comput., 37 (1981), pp. 141158.Google Scholar
[22] Liu, W. K., Jun, S., Li, S., Adee, J. and Belytschko, T., Reproducing kernel particle methods for structural dynamics, Int. J. Num. Meth. Eng., 5(3) (1995), pp. 16551679.Google Scholar
[23] Liu, W. K., Chen, Y., Jun, S., Chen, J. S., Belytschko, T., Pan, C., Uras, R. A. and Chang, C. T., Overview and applications of the reproducing kernel particle method, Arch. Comput. Meth. Eng., 3(1) (1996), pp. 380.CrossRefGoogle Scholar
[24] Madzvamuse, A., A Numerical Approach to the Study of Spatial Pattern Formation, Ph.D. Thesis, University of Oxford, 2000.Google Scholar
[25] Madzvamuse, A., Wathen, A. and Maini, P., A moving grid finite element method for the simulation of pattern generation by Turing models on growing domains, J. Sci. Comput., 24 (2005), pp. 247262.Google Scholar
[26] Madzvamuse, A., Wathen, A. and Maini, P., A moving grid finite element method applied to a model biological pattern generator, J. Comput. Phys., 190 (2003), pp. 478500.Google Scholar
[27] Madzvamuse, A. and Maini, P., Velocity-induced numerical solution of reaction-diffusion systems on continuously growing domains, J. Comput. Phys., 225 (2007), pp. 100119.Google Scholar
[28] Meinhardt, H., Models of Biological Pattern Formation, Academic Press, New York, 1982.Google Scholar
[29] Melenk, J. M. and Babuska, I., The partition of unity finite element method: Basic theory and applications, Comput. Methods Appl. Mech. Eng., 139 (1996), pp. 289314.Google Scholar
[30] Monaghan, J. J., Smoothed particle hydrodynamics: Some recent improvement and applications, Annu. Rev. Astron. Phys., 30 (1992), pp. 543574.CrossRefGoogle Scholar
[31] Murray, J. D., A prepattern formation mechanism for animal coat markings, J. Theor. Biol., 88 (1981), pp. 161199.Google Scholar
[32] Murray, J. D., Mathematical Biology, Springer, Heidelberg, New York, 1993.Google Scholar
[33] Nayroles, B., Touzot, G. and Villon, P., Generalizing the FEM: Diffuse approximation and diffuse elements, Comput. Mech., 10 (1992), pp. 307318.Google Scholar
[34] Oñate, E., Idelsohn, S., Zienkiewicz, O. C. and Fisher, T., Finite point method for analysis of fluid flow problems, Proceedings of the 9th Int. Conference on Finite Element Methods in Fluids. Venize, Italy, October, 1995, 15-21.Google Scholar
[35] Oñate, E., Idelsohn, S., Zienkiewicz, O. C. and Taylor, R. L., A finite point method in computational mechanics, Applications to convective transport and fluid flow, Int. J. Num. Meth. Eng., 39 (1996), pp. 38393866.Google Scholar
[36] Randles, P. W. and Libersky, L. D., Smoothed particle hydrodynamics: Some recent improvement and applications, Comput. Methods Appl. Mech. Eng., 139 (1996), pp. 375408.CrossRefGoogle Scholar
[37] Shakeri, F. and Dehghan, M., The finite volume spectral element method to solve Turing models in the biological pattern formation, J. Comput. Math. Appl., 32 (2011), pp. 43224336.Google Scholar
[38] Schnakenberg, J., Simple chemical reaction systems with limit cycle behavior, J. Theoret. Biol., 81 (1979), pp. 389400.Google Scholar
[39] Tatari, M., Kamranian, M. and Dehghan, M., The finite point method for reaction-diffusion systems in developmental biology, CMES., 82(1) (2011), pp. 127.Google Scholar
[40] Thomas, D., Artificial enzyme membrane, transport, memory and oscillatory phenomena, in: Thomas, D., Kervenez, J.-P. (Eds.), Analysis and Control of Immobilised Enzyme Systems, Springer, Berlin, Heidelberg, New York, (1975), pp. 115150.Google Scholar
[41] Turing, A., The chemical basis of morphogenesis, Philos. Trans. Roy. Soc. London, 237 (1952), pp. 3772.Google Scholar
[42] Yi, F., Wei, J. and Shi, J., Bifurcation and spatiotemporal patterns in a homogeneous diffusive predator-prey system, J. Differ. Equation, 246(5) (2009), pp. 19441977.Google Scholar
[43] Yaw, L. L., Co-Rotational Meshfree Formulation for Large Deformation Inelastic Analysis of Two Dimensional Structural Systems, Ph.D. Thesis, University of California, 2008.Google Scholar
[44] Zhu, T., D Zhang, J. and Atluri, S. N., A local boundary integral equation (lbie) method in computational mechanics, and a meshless discretization approach, Comput. Mech., 21 (1998), pp. 223235.Google Scholar
[45] Zhu, T., Zhang, J. D. and Atluri, S. N., A meshless local boundary integral equation (lbie) method for solving nonlinear problems, Comput. Mech., 22 (1998), pp. 174186.Google Scholar