A Petrov-Galerkin Spectral Element Method for Fractional Elliptic Problems

TL;DR

This paper introduces a novel Petrov-Galerkin spectral element method for one-dimensional fractional elliptic problems, improving accuracy and efficiency in handling singular solutions and non-local effects.

Contribution

The paper develops a new $C^{0}$-continuous Petrov-Galerkin spectral element method with efficient assembly and non-local matrix computation for fractional elliptic problems, including strategies for singular solutions.

Findings

Better-conditioned system with local basis/test functions.

Accurate capture of singular solutions using non-uniform grids.

Enhanced efficiency through partial history fading.

Abstract

We develop a new $C^{\,0}$-continuous Petrov-Galerkin spectral element method for one-dimensional fractional elliptic problems of the form ${}_{0}{\mathcal{D}}_{x}^{\alpha} u(x) - \lambda u(x) = f(x)$, $\alpha \in (1,2]$, subject to homogeneous boundary conditions. We employ the standard (modal) spectral element bases and the Jacobi poly-fractonomials as the test functions [1]. We formulate a new procedure for assembling the global linear system from elemental (local) mass and stiffness matrices. The Petrov-Galerkin formulation requires performing elemental (local) construction of mass and stiffness matrices in the standard domain only once. Moreover, we efficiently obtain the non-local (history) stiffness matrices, in which the non-locality is presented analytically for uniform grids. We also investigate two distinct choices of basis/test functions: i) local basis/test functions, and ii) local basis with global test functions. We show that the former choice leads to a better-conditioned system and accuracy. We consider smooth and singular solutions, where the singularity can occur at boundary points as well as in the interior domain. We also construct two non-uniform grids over the whole computational domain in order to capture singular solutions. Finally, we perform a systematic numerical study of non-local effects via full and partial history fading in order to further enhance the efficiency of the scheme.