Abstract

Fractional partial differential equations with time-space fractional derivatives describe some important physical phenomena. For example, the subdiffusion equation (time order 0<α<1) is more suitable to describe the phenomena of charge carrier transport in amorphous semiconductors, nuclear magnetic resonance (NMR) diffusometry in percolative, Rouse, or reptation dynamics in polymeric systems, the diffusion of a scalar tracer in an array of convection rolls, or the dynamics of a bead in a polymeric network, and so on. However, the superdiffusion case (1<α<2) is more accurate to depict the special domains of rotating flows, collective slip diffusion on solid surfaces, layered velocity fields, Richardson turbulent diffusion, bulk-surface exchange controlled dynamics in porous glasses, the transport in micelle systems and heterogeneous rocks, quantum optics, single molecule spectroscopy, the transport in turbulent plasma, bacterial motion, and even for the flight of an albatross (for more physical applications of fractional sub-super diffusion equations, one can see Metzler and Klafter in 2000). In this work, we establish two fully discrete numerical schemes for solving a class of nonlinear time-space fractional subdiffusion/superdiffusion equations by using backward Euler difference 1<α<2 or second-order central difference 1<α<2/local discontinuous Galerkin finite element mixed method. By introducing the mathematical induction method, we show the concrete analysis for the stability and the convergence rate under the L2 norm of the two LDG schemes. In the end, we adopt several numerical experiments to validate the proposed model and demonstrate the features of the two numerical schemes, such as the optimal convergence rate in space direction is close to Ohk+1. The convergence rate in time direction can arrive at Oτ2−α when the fractional derivative is 0<α<1. If the fractional derivative parameter is 1<α<2 and we choose the relationship as h=C′τ (h denotes the space step size, C′ is a constant, and τ is the time step size), then the time convergence rate can reach to Oτ3−α. The experiment results illustrate that the proposed method is effective in solving nonlinear time-space fractional subdiffusion/superdiffusion equations.

Highlights

  • Over the past several decades, fractional differential equations attract more and more scholar’s attention due to their wide applications in science and engineering [1,2,3,4]

  • The space-time fractional diffusion equation we mean is an evolution equation; they imply for the flux fractional Fick’s law which accounts for spatial and temporal nonlocality. e fundamental solution of this type of fractional diffusion equation can be used to interpret a probability density evolving in time of a peculiar self-similar stochastic process, and we view it as a generalized diffusion process [5]

  • In order to prove the convergence rate of two fully discrete local discontinuous Galerkin (LDG) numerical schemes better, we briefly list some relevant properties of fractional integrals and derivatives as well as several basic lemmas that are needed as follows; some of them have already been proved in [24]. erefore, we ignore the detailed proof processes here

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Summary

Introduction

Over the past several decades, fractional differential equations attract more and more scholar’s attention due to their wide applications in science and engineering [1,2,3,4]. The space-time fractional diffusion equation we mean is an evolution equation; they imply for the flux fractional Fick’s law which accounts for spatial and temporal nonlocality. E fundamental solution (for the Cauchy problem) of this type of fractional diffusion equation can be used to interpret a probability density evolving in time of a peculiar self-similar stochastic process, and we view it as a generalized diffusion process [5]. Fractional subdiffusion/ superdiffusion equations (FSEs) play important roles in describing a special type of anomalous diffusion process, and become very popular for many real applications [6, 7]. It is of great importance to seek efficient methods to solve fractional subdiffusion/superdiffusion equations (FSEs). Generally speaking, it is difficult to obtain the analytic solutions for most of the fractional differential

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