  The objective of this study is to address the difficulty of simplifying the
geometric model in which a differential problem is formulated, also called
defeaturing, while simultaneously ensuring that the accuracy of the solution is
maintained under control. This enables faster and more efficient simulations,
without sacrificing accuracy. More precisely, we consider an isogeometric
discretisation of an elliptic model problem defined on a two-dimensional
hierarchical B-spline computational domain with a complex boundary. Starting
with an oversimplification of the geometry, we build a goal-oriented adaptive
strategy that adaptively reintroduces continuous geometrical features in
regions where the analysis suggests a large impact on the quantity of interest.
This strategy is driven by an a posteriori estimator of the defeaturing error
based on first-order shape sensitivity analysis, and it profits from the local
refinement properties of hierarchical B-splines. The adaptive algorithm is
described together with a procedure to generate (partially) simplified
hierarchical B-spline geometrical domains. Numerical experiments are presented
to illustrate the proposed strategy and its limitations.
