Abstract
AbstractWe discuss a computational multiscale method for the efficient simulation and optimization of differential equations with multiple scales in time. The approach is based on isolating the influences of the fast scale by a local periodic‐in‐time assumption that allows for time‐stepping of the averaged slow scale with very large step sizes. For this approach we develop a variational formulation that gives easy access to the methodology of goal‐oriented error estimation and adaptivity as well as gradient based optimization.
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