Analysis of the weighted shifted boundary method for the Poisson and Stokes problems
The Shifted Boundary Method (SBM) belongs to the class of unfitted (or immersed, or embedded) finite element methods, and relies on reformulating the original boundary value problem over a surrogate (approximate) computational domain. Accuracy is maintained by properly shifting the location and values of the boundary conditions. This avoids integration over cut cells and the associated implementation issues. Recently, the Weighted SBM (WSBM) was proposed for the Navier-Stokes equations with free surfaces and the Stokes flow with moving boundaries. The attribute “weighted” in the name WSBM stems from the fact that its variational form is weighted with the elemental volume fraction of active fluid. The motivation for the development of the WSBM was the preservation of the volume of active fluid to a higher degree of accuracy, which in turn resulted in improved stability and robustness characteristics in moving-boundary, time-dependent simulations. In this article, we present the numerical analysis of the WSBM formulations for the Poisson and Stokes problems. We give mathematical conditions under which the bilinear forms defining the discrete variational formulations are uniformly coercive (Poisson problem) or inf-sup stable (Stokes problem). By these results, stability and optimal convergence is proven in the natural norm; L 2-error estimates can also be derived.
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- Numerical & Computational Mathematics
- 49 Mathematical sciences
- 46 Information and computing sciences
- 35 Commerce, management, tourism and services
- 15 Commerce, Management, Tourism and Services
- 08 Information and Computing Sciences
- 01 Mathematical Sciences
Citation
Published In
DOI
ISSN
Publication Date
Volume
Start / End Page
Related Subject Headings
- Numerical & Computational Mathematics
- 49 Mathematical sciences
- 46 Information and computing sciences
- 35 Commerce, management, tourism and services
- 15 Commerce, Management, Tourism and Services
- 08 Information and Computing Sciences
- 01 Mathematical Sciences