1,181 research outputs found
Efficient Multigrid Preconditioners for Atmospheric Flow Simulations at High Aspect Ratio
Many problems in fluid modelling require the efficient solution of highly
anisotropic elliptic partial differential equations (PDEs) in "flat" domains.
For example, in numerical weather- and climate-prediction an elliptic PDE for
the pressure correction has to be solved at every time step in a thin spherical
shell representing the global atmosphere. This elliptic solve can be one of the
computationally most demanding components in semi-implicit semi-Lagrangian time
stepping methods which are very popular as they allow for larger model time
steps and better overall performance. With increasing model resolution,
algorithmically efficient and scalable algorithms are essential to run the code
under tight operational time constraints. We discuss the theory and practical
application of bespoke geometric multigrid preconditioners for equations of
this type. The algorithms deal with the strong anisotropy in the vertical
direction by using the tensor-product approach originally analysed by B\"{o}rm
and Hiptmair [Numer. Algorithms, 26/3 (2001), pp. 219-234]. We extend the
analysis to three dimensions under slightly weakened assumptions, and
numerically demonstrate its efficiency for the solution of the elliptic PDE for
the global pressure correction in atmospheric forecast models. For this we
compare the performance of different multigrid preconditioners on a
tensor-product grid with a semi-structured and quasi-uniform horizontal mesh
and a one dimensional vertical grid. The code is implemented in the Distributed
and Unified Numerics Environment (DUNE), which provides an easy-to-use and
scalable environment for algorithms operating on tensor-product grids. Parallel
scalability of our solvers on up to 20,480 cores is demonstrated on the HECToR
supercomputer.Comment: 22 pages, 6 Figures, 2 Table
Multi-stage high order semi-Lagrangian schemes for incompressible flows in Cartesian geometries
Efficient transport algorithms are essential to the numerical resolution of
incompressible fluid flow problems. Semi-Lagrangian methods are widely used in
grid based methods to achieve this aim. The accuracy of the interpolation
strategy then determines the properties of the scheme. We introduce a simple
multi-stage procedure which can easily be used to increase the order of
accuracy of a code based on multi-linear interpolations. This approach is an
extension of a corrective algorithm introduced by Dupont \& Liu (2003, 2007).
This multi-stage procedure can be easily implemented in existing parallel codes
using a domain decomposition strategy, as the communications pattern is
identical to that of the multi-linear scheme. We show how a combination of a
forward and backward error correction can provide a third-order accurate
scheme, thus significantly reducing diffusive effects while retaining a
non-dispersive leading error term.Comment: 14 pages, 10 figure
On the error propagation of semi-Lagrange and Fourier methods for advection problems
In this paper we study the error propagation of numerical schemes for the
advection equation in the case where high precision is desired. The numerical
methods considered are based on the fast Fourier transform, polynomial
interpolation (semi-Lagrangian methods using a Lagrange or spline
interpolation), and a discontinuous Galerkin semi-Lagrangian approach (which is
conservative and has to store more than a single value per cell).
We demonstrate, by carrying out numerical experiments, that the worst case
error estimates given in the literature provide a good explanation for the
error propagation of the interpolation-based semi-Lagrangian methods. For the
discontinuous Galerkin semi-Lagrangian method, however, we find that the
characteristic property of semi-Lagrangian error estimates (namely the fact
that the error increases proportionally to the number of time steps) is not
observed. We provide an explanation for this behavior and conduct numerical
simulations that corroborate the different qualitative features of the error in
the two respective types of semi-Lagrangian methods.
The method based on the fast Fourier transform is exact but, due to round-off
errors, susceptible to a linear increase of the error in the number of time
steps. We show how to modify the Cooley--Tukey algorithm in order to obtain an
error growth that is proportional to the square root of the number of time
steps.
Finally, we show, for a simple model, that our conclusions hold true if the
advection solver is used as part of a splitting scheme.Comment: submitted to Computers & Mathematics with Application
An efficient parallel immersed boundary algorithm using a pseudo-compressible fluid solver
We propose an efficient algorithm for the immersed boundary method on
distributed-memory architectures, with the computational complexity of a
completely explicit method and excellent parallel scaling. The algorithm
utilizes the pseudo-compressibility method recently proposed by Guermond and
Minev [Comptes Rendus Mathematique, 348:581-585, 2010] that uses a directional
splitting strategy to discretize the incompressible Navier-Stokes equations,
thereby reducing the linear systems to a series of one-dimensional tridiagonal
systems. We perform numerical simulations of several fluid-structure
interaction problems in two and three dimensions and study the accuracy and
convergence rates of the proposed algorithm. For these problems, we compare the
proposed algorithm against other second-order projection-based fluid solvers.
Lastly, the strong and weak scaling properties of the proposed algorithm are
investigated
Hybrid spectral-particle method for the turbulent transport of a passive scalar
International audienceThis paper describes a novel hybrid method, combining a spectral and a particle method, to simulate the turbulent transport of a passive scalar. The method is studied from the point of view of accuracy and numerical cost. It leads to a significative speed up over more conventional grid-based methods and allows to address challenging Schmidt numbers. In particular, theoretical predictions of universal scaling in forced homogeneous turbulence are recovered for a wide range of Schmidt numbers for large, intermediate and small scales of the scalar
A mass-conserving sparse grid combination technique with biorthogonal hierarchical basis functions for kinetic simulations
The exact numerical simulation of plasma turbulence is one of the assets and
challenges in fusion research. For grid-based solvers, sufficiently fine
resolutions are often unattainable due to the curse of dimensionality. The
sparse grid combination technique provides the means to alleviate the curse of
dimensionality for kinetic simulations. However, the hierarchical
representation for the combination step with the state-of-the-art hat functions
suffers from poor conservation properties and numerical instability.
The present work introduces two new variants of hierarchical multiscale basis
functions for use with the combination technique: the biorthogonal and full
weighting bases. The new basis functions conserve the total mass and are shown
to significantly increase accuracy for a finite-volume solution of constant
advection. Further numerical experiments based on the combination technique
applied to a semi-Lagrangian Vlasov--Poisson solver show a stabilizing effect
of the new bases on the simulations
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