A semi-discrete finite element method for a class of time-fractional diffusion equations

TL;DR

This paper introduces a semi-discrete finite element method that efficiently solves time-fractional diffusion equations by reducing long-time computational challenges, demonstrated through multiple examples and real-world groundwater transport modeling.

Contribution

It presents a semi-analytical finite element approach that overcomes long-time computation issues in time-fractional diffusion equations, enhancing efficiency and accuracy.

Findings

Effective reduction of long-time computation in fractional diffusion equations

Accurate modeling of anomalous transport in groundwater

Method validated with real-world aquifer data

Abstract

As fractional diffusion equations can describe the early breakthrough and the heavy-tail decay features observed in anomalous transport of contaminants in groundwater and porous soil, they have been commonly employed in the related mathematical descriptions. These models usually involve long-time range computation, which is a critical obstacle for its application, improvement of the computational efficiency is of great significance. In this paper, a semi-analytical method is presented for solving a class of time-fractional diffusion equations which overcomes the critical long-time range computation problem of time fractional differential equations. In the procedure, the spatial domain is discretized by the finite element method which reduces the fractional diffusion equations into approximate fractional relaxation equations. As analytical solutions exist for the latter equations, the burden arising from long-time range computation can effectively be minimized. To illustrate its efficiency and simplicity, four examples are presented. In addition, the method is employed to solve the time-fractional advection-diffusion equation characterizing the bromide transport process in a fractured granite aquifer. The prediction closely agrees with the experimental data and the heavy-tail decay of anomalous transport process is well-represented.