Convergence of iterative methods based on Neumann series for composite materials: theory and practice

TL;DR

This paper analyzes the convergence properties of iterative Fourier-based methods for calculating fields in composite materials, highlighting the influence of singularities, discretization, and microstructure on accuracy and convergence.

Contribution

It provides a theoretical and numerical analysis of the convergence behavior of Neumann series-based iterative FFT methods for composite materials.

Findings

Convergence depends on the singularity structure of the effective tensor function.

Numerical results show limited iterations are practical due to accuracy loss.

Discretization size significantly affects the accuracy of the methods.

Abstract

Iterative Fast Fourier Transform methods are useful for calculating the fields in composite materials and their macroscopic response. By iterating back and forth until convergence, the differential constraints are satisfied in Fourier space, and the constitutive law in real space. The methods correspond to series expansions of appropriate operators and to series expansions for the effective tensor as a function of the component moduli. It is shown that the singularity structure of this function can shed much light on the convergence properties of the iterative Fast Fourier Transform methods. We look at a model example of a square array of conducting square inclusions for which there is an exact formula for the effective conductivity (Obnosov). Theoretically some of the methods converge when the inclusions have zero or even negative conductivity. However, the numerics do not always confirm this extended range of convergence and show that accuracy is lost after relatively few iterations. There is little point in iterating beyond this. Accuracy improves when the grid size is reduced, showing that the discrepancy is linked to the discretization. Finally, it is shown that none of the three iterative schemes investigated over-performs the others for all possible microstructures and all contrasts.