Next Article in Journal
Adaptive Metrics for Adaptive Samples
Previous Article in Journal
Pavement Defect Segmentation in Orthoframes with a Pipeline of Three Convolutional Neural Networks
Open AccessFeature PaperArticle

Scalable Block Preconditioners for Linearized Navier-Stokes Equations at High Reynolds Number

1
School of Mathematics, University of Edinburgh, Edinburgh EH9 3FD, UK
2
Department of Civil Environmental and Architectural Engineering, University of Padua, 35122 Padova, Italy
*
Author to whom correspondence should be addressed.
Algorithms 2020, 13(8), 199; https://doi.org/10.3390/a13080199
Received: 21 July 2020 / Revised: 12 August 2020 / Accepted: 14 August 2020 / Published: 16 August 2020
We review a number of preconditioners for the advection-diffusion operator and for the Schur complement matrix, which, in turn, constitute the building blocks for Constraint and Triangular Preconditioners to accelerate the iterative solution of the discretized and linearized Navier-Stokes equations. An intensive numerical testing is performed onto the driven cavity problem with low values of the viscosity coefficient. We devise an efficient multigrid preconditioner for the advection-diffusion matrix, which, combined with the commuted BFBt Schur complement approximation, and inserted in a 2×2 block preconditioner, provides convergence of the Generalized Minimal Residual (GMRES) method in a number of iteration independent of the meshsize for the lowest values of the viscosity parameter. The low-rank acceleration of such preconditioner is also investigated, showing its great potential. View Full-Text
Keywords: scalable preconditioners; Navier-Stokes equations; GMRES method; low-rank updates; multigrid scalable preconditioners; Navier-Stokes equations; GMRES method; low-rank updates; multigrid
Show Figures

Figure 1

MDPI and ACS Style

Zanetti, F.; Bergamaschi, L. Scalable Block Preconditioners for Linearized Navier-Stokes Equations at High Reynolds Number. Algorithms 2020, 13, 199. https://doi.org/10.3390/a13080199

AMA Style

Zanetti F, Bergamaschi L. Scalable Block Preconditioners for Linearized Navier-Stokes Equations at High Reynolds Number. Algorithms. 2020; 13(8):199. https://doi.org/10.3390/a13080199

Chicago/Turabian Style

Zanetti, Filippo; Bergamaschi, Luca. 2020. "Scalable Block Preconditioners for Linearized Navier-Stokes Equations at High Reynolds Number" Algorithms 13, no. 8: 199. https://doi.org/10.3390/a13080199

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop