Analysis of A New Adaptive Time Filter Algorithm for The Unsteady Stokes/Darcy Model

TL;DR

This paper introduces an adaptive time filter algorithm that enhances the convergence order of numerical solutions for the unsteady Stokes/Darcy model, combining stability analysis and numerical verification.

Contribution

It presents a novel adaptive time filter method that improves the order of accuracy for the unsteady Stokes/Darcy model without significant computational overhead.

Findings

The algorithm achieves second-order convergence.

Numerical experiments confirm stability and efficiency.

Adaptive methods outperform fixed-step approaches.

Abstract

In this report, we propose a new adaptive time filter algorithm for the unsteady Stokes/Darcy model. First we present a first order ${\theta}$-scheme with the variable time step which is one parameter family of Linear Multi-step methods and use a time filter algorithm to increase the convergence order to second order with almost no increasing the amount of computation. Furthermore, we construct coupled and decoupled adaptive algorithms. Then we analyze stabilities and the second-order accuracy of variable time-stepping algorithm for Linear Multi-step methods plus time filter, respectively. Finally, we use two numerical experiments to verify theoretical results including effectiveness, convergence and efficiency with adaptive method.