Multiscale Modeling and Simulation · 2019 · 19 citations · 13 references
ComputingComputational EngineeringComputer ScienceComputational Fluid DynamicsParallel AlgorithmsParallel ComputingConvergence AnalysisError EstimationHomogenization MethodsParallel Numerical MethodsPartial Differential EquationsTime IntegrationElliptic Partial Differential EquationsError Estimation For Time-dependent ProblemsHomogenizationLocal Error IndicatorsLocalized Orthogonal DecompositionNumerical HomogenizationPetrov-galerkin DiscretizationStochastic Integration
We consider a sequence of elliptic partial differential equations (PDEs) with different but similar rapidly varying coefficients. Such sequences appear, for example, in splitting schemes for time-dependent problems (with one coefficient per time step) and in sample based stochastic integration of outputs from an elliptic PDE (with one coefficient per sample member). We propose a parallelizable algorithm based on Petrov--Galerkin localized orthogonal decomposition that adaptively (using computable and theoretically derived error indicators) recomputes the local corrector problems only where it improves accuracy. The method is illustrated in detail by an example of a time-dependent two-pase Darcy flow problem in three dimensions.
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