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This paper introduces a novel recursive time-filtering framework designed to elevate the second-order filtered backward Euler (FBE) method to third-order accuracy while preserving its inherent computational simplicity. While FBE remains a staple in computational science due to its robust stability, its second-order convergence often necessitates prohibitively small time steps for high-fidelity simulations. We resolve this by proposing a non-intrusive extension that functions as a modular post-processing step, requiring no additional implicit solves or structural modifications to existing numerical solvers. By leveraging principles from discrete differential geometry, we generalize the framework to variable time-step regimes through a rigorous definition of discrete curvature based on quadratic interpolants. The theoretical foundation involves recasting the FBE scheme into its one-leg equivalent and applying the framework of linear multistep methods (LMM). Through a derivation of the local truncation error (LTE), we identify a unique, step-dependent filtering parameter
This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)
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