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Local modifications of a computational domain are often performed in order tosimplify the meshing process and to reduce computational costs and memoryrequirements. However, removing geometrical features of a domain oftenintroduces a non-negligible error in the solution of a differential problem inwhich it is defined. In this work, we extend the results from [1] by studyingthe case of domains containing an arbitrary number of distinct Neumannfeatures, and by performing an analysis on Poisson's, linear elasticity, andStokes' equations. We introduce a simple, computationally cheap, reliable, andefficient a posteriori estimator of the geometrical defeaturing error.Moreover, we also introduce a geometric refinement strategy that accounts forthe defeaturing error: Starting from a fully defeatured geometry, the algorithmdetermines at each iteration step which features need to be added to thegeometrical model to reduce the defeaturing error. These important features arethen added to the (partially) defeatured geometrical model at the nextiteration, until the solution attains a prescribed accuracy. A wide range oftwo- and three-dimensional numerical experiments are finally reported toillustrate this work.

Analysis-aware defeaturing of complex geometries with Neumann features