An augmented Lagrangian preconditioner for the 3D stationary incompressible Navier-Stokes equations at high Reynolds number
- Submitting institution
-
University of Durham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 119066
- Type
- D - Journal article
- DOI
-
10.1137/18M1219370
- Title of journal
- SIAM Journal on Scientific Computing
- Article number
- -
- First page
- A3073
- Volume
- 41
- Issue
- 5
- ISSN
- 10648275
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2019
- URL
-
https://doi.org/10.1137/18M1219370
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
A - Innovative Computing
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- First preconditioner for the 3D incompressible stationary Navier-Stokes equations with both optimal algorithmic complexity, and performance robust to the Reynolds number. Simulation of the Navier-Stokes equations underpins all of computational fluid dynamics. Prior to this work, no robust, scalable solver for these important equations was known in three-dimensions. Presented as an invited plenary at Preconditioning 2019. Computational results with up to 1 billion degrees of freedom, results validated against known test cases. All software open source and released as part of the Firedrake (www.firedrakeproject.org) and PETSc libraries (www.mcs.anl.gov/petsc).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -