A post-processed higher-order multiscale method for nondivergence-form elliptic equations
For computational scientists solving PDEs with heterogeneous coefficients, this method offers higher-order accuracy where previous approaches were limited by low regularity.
The paper develops a multiscale finite element method for nondivergence-form elliptic equations with highly heterogeneous coefficients, achieving higher-order convergence rates through a novel post-processing strategy. Numerical experiments confirm improved performance.
We study the finite element approximation of linear second-order elliptic partial differential equations in nondivergence form with highly heterogeneous diffusion and drift coefficients. A generalized Cordes condition is imposed to guarantee that a suitably renormalized version of the nondivergence-form differential operator is near the Laplacian. Based on a stabilized symmetric formulation for the gradient that enables the use of $H^1$-conforming approximation spaces, we construct a multiscale method following the methodology of the localized orthogonal decomposition with coarse basis functions tailored to the heterogeneous coefficients. We employ a novel post-processing strategy to obtain higher-order convergence rates, overcoming previous limitations imposed by the low regularity of the load functional. Numerical experiments demonstrate the performance of the method.