Reduced order modelling of nonlinear cross-diffusion systems

TL;DR

This paper develops a reduced-order modeling approach for nonlinear cross-diffusion systems from population dynamics, specifically the SKT equation, using POD and tensorial POD to efficiently simulate pattern formation with improved accuracy.

Contribution

The paper introduces a time-windowed POD approach for nonlinear cross-diffusion equations, enhancing accuracy over traditional global POD methods.

Findings

Reduced-order solutions are more accurate with time-windowed POD.

The method accelerates computations using tensorial POD.

Numerical results show decreased entropy, indicating better stability.

Abstract

In this work, we present a reduced-order model for a nonlinear cross-diffusion problem from population dynamics, for the Shigesada-Kawasaki-Teramoto (SKT) equation with Lotka-Volterra kinetics. The finite-difference discretization of the SKT equation in space results in a system of linear--quadratic ordinary differential equations (ODEs). The reduced order model (ROM) has the same linear-quadratic structure as the full order model (FOM). Using the linear-quadratic structure of the ROM, the reduced-order solutions are computed independent of the full solutions with the proper orthogonal decomposition (POD). The computation of the reduced solutions is further accelerated by applying tensorial POD. The formation of the patterns of the SKT equation consists of a fast transient phase and a long steady-state phase. Reduced order solutions are computed by separating the time, into two-time intervals. In numerical experiments, we show for one-and two-dimensional SKT equations with pattern formation, the reduced-order solutions obtained in the time-windowed form, i.e., principal decomposition framework (P-POD), are more accurate than the global POD solutions (G-POD) obtained in the whole time interval. Furthermore, we show the decrease of the entropy numerically by the reduced solutions, which is important for the global existence of nonlinear cross-diffusion equations such as the SKT equation.