Error Estimates for Nitsche's Method on Approximate Domains
This work addresses the challenge of geometric approximation effects on convergence in Nitsche-based finite element methods, particularly for unfitted discretizations, but it is incremental as it refines existing error analysis frameworks.
The paper tackles the problem of deriving error estimates for Nitsche's method on approximate domains, such as in unfitted finite element methods, by quantifying geometric errors in terms of boundary location and normal perturbations. The results include an energy norm estimate with an h^{-1/2} amplification of boundary location error, a refined H^1-seminorm estimate that removes this amplification, and an optimal order L^2-error estimate with decoupled geometry contributions.
We derive a priori error estimates for Nitsche's method applied to elliptic problems on approximate domains. Such approximations arise, for example, in unfitted finite element methods, data-driven simulations, and evolving domain problems, where the computational domain does not coincide exactly with the physical one. We quantify geometric errors in terms of boundary location and normal perturbations and carry out the analysis in an abstract CutFEM framework under standard stability assumptions. In the energy norm, we obtain an estimate exhibiting an $h^{-1/2}$ amplification of the boundary location error. We then prove a refined $H^1$-seminorm estimate that removes this amplification, yielding a sharper bound with additive contributions from boundary location and normal errors. Finally, we establish an optimal order $L^2$-error estimate based on a refined duality argument, where the geometry contribution appears as a separate additive term, decoupled from the mesh size $h$. The results reveal a fundamental distinction between the norms: the energy norm amplifies boundary location errors while remaining insensitive to normal perturbations, the $H^1$-seminorm separates location and normal errors, and the $L^2$-norm is insensitive to normal perturbations. This provides a clear characterization of how geometric approximation affects convergence in Nitsche-based finite element methods, with particular relevance for unfitted discretizations.