Abstract

In this paper we present a robust, efficient and accurate finite element method for solving reaction–diffusion systems on stationary spheroidal surfaces (these are surfaces which are deformations of the sphere such as ellipsoids, dumbbells, and heart-shaped surfaces) with potential applications in the areas of developmental biology, cancer research, wound healing, tissue regeneration, and cell motility among many others where such models are routinely used. Our method is inspired by the radially projected finite element method introduced in [39]. (Hence the name “projected” finite element method.) The advantages of the projected finite element method are that it is easy to implement and that it provides a conforming finite element discretization which is “logically” rectangular. To demonstrate the robustness, applicability and generality of this numerical method, we present solutions of reaction–diffusion systems on various spheroidal surfaces. We show that the method presented in this paper preserves positivity of the solutions of reaction–diffusion equations which is not generally true for Galerkin type methods. We conclude that surface geometry plays a pivotal role in pattern formation. For a fixed set of model parameter values, different surfaces give rise to different pattern generation sequences of either spots or stripes or a combination (observed as circular spot-stripe patterns). These results clearly demonstrate the need for detailed theoretical analytical studies to elucidate how surface geometry and curvature influence pattern formation on complex surfaces.

Highlights

  • For many centuries, the problem of pattern formation has fascinated experimentalists and theoreticians alike

  • The majority of studies for pattern formation by reaction–diffusion equations (RDEs) to date have studied RDEs on planar domains [34,36,37,41,45]. This is perfectly justifiable in some biological species such as butterfly patterns [47], and stingrays [2], it is not for many species such as snakes, eel, fish, and leopards [41] where surface geometry and curvature play a crucial role in the emergence and orientation of patterns on biologically realistic surfaces

  • The PFEM proposed in this article is inspired by the radially projected finite element method which was used to compute approximate numerical solutions for partial differential equations on stationary spheroidal surfaces such as spheres, ellipsoids, and tori [39,52]

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Summary

Introduction

The problem of pattern formation has fascinated experimentalists and theoreticians alike. The PFEM proposed in this article is inspired by the radially projected finite element method which was used to compute approximate numerical solutions for partial differential equations on stationary spheroidal surfaces such as spheres, ellipsoids, and tori [39,52]. The PFEM gives a geometrically exact discretization of spheroidal surfaces (the geometry is not approximated, but represented exactly) This is attractive for numerical simulations since the resulting finite element discretization is conforming and is “logically rectangular.”.

Model equations on stationary spheroidal surfaces
Preliminaries
Weak formulation of the reaction–diffusion system
Space and time-discretizations
Approximation properties
Preservation of the invariant region
Parallel computing
Convergence rates
Picard iteration
Sphere
Ellipsoid
The effect of varying γ on pattern formation
Full Text
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