A posteriori error estimation and anisotropy detection with the dual-weighted residual method
In this work we develop a new framework for a posteriori error estimation and detection of anisotropies based on the dual-weighted residual (DWR) method by Becker and Rannacher. The common approach for anisotropic mesh adaptation is to analyze the Hessian of the solution. Eigenvalues and eigenvector...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article (Journal) |
| Language: | English |
| Published: |
10 January 2010
|
| In: |
International journal for numerical methods in fluids
Year: 2010, Volume: 62, Issue: 1, Pages: 90-118 |
| ISSN: | 1097-0363 |
| DOI: | 10.1002/fld.2016 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1002/fld.2016 Verlag, lizenzpflichtig, Volltext: https://onlinelibrary.wiley.com/doi/abs/10.1002/fld.2016 
|
| Author Notes: | Thomas Richter |
| Summary: | In this work we develop a new framework for a posteriori error estimation and detection of anisotropies based on the dual-weighted residual (DWR) method by Becker and Rannacher. The common approach for anisotropic mesh adaptation is to analyze the Hessian of the solution. Eigenvalues and eigenvectors indicate dominant directions and optimal stretching of elements. However, this approach is firmly linked to energy norm error estimation. Here, we extend the DWR method to anisotropic finite elements allowing for the direct estimation of directional errors with regard to given output functionals. The resulting meshes reflect anisotropic properties of both the solution and the functional. For the optimal measurement of the directional errors, the coarse meshes need some alignment with the dominant anisotropies. Numerical examples will demonstrate the efficiency of this method on various three-dimensional problems including a well-known Navier-Stokes benchmark. Copyright © 2009 John Wiley & Sons, Ltd. |
|---|---|
| Item Description: | Online veröffentlicht 26. Februar 2009 Gesehen am 15.05.2023 |
| Physical Description: | Online Resource |
| ISSN: | 1097-0363 |
| DOI: | 10.1002/fld.2016 |