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Kars Knook

Publications and source records attributed to Kars Knook.

3 recordsLinked to original sources

Preconditioners for the Onsager-Stefan-Maxwell equations for multicomponent diffusion

The Onsager-Stefan-Maxwell (OSM) equations are an important model of mass transport in multicomponent flows with multiple chemical species. They describe the coupling of diffusive fluxes between species, accounting for their interactions through frictional and thermodynamic driving forces. In this work we propose an augmented Lagrangian preconditioner and prove its discretization-robustness for a Picard linearization of the stationary OSM equations in the isobaric, isothermal, ideal gaseous setting. For the Newton linearization we employ the augmented Lagrangian preconditioner as a block diagonal smoother inside a monolithic geometric multigrid iteration and combine with vertex star Schwarz methods. This strategy is shown to be applicable in a wide variety of settings which incorporate cross-diffusion, nonideal mixing, thermal, pressure, convective, and electrochemical effects. We demonstrate robustness or mild dependence with respect to mesh refinement and polynomial degree of the proposed monolithic preconditioning strategy for different types of multicomponent flows in several applications: cross-diffusion in the human airways, separation of gases under a temperature gradient, nonideal mixing of benzene and cyclohexane, and electrolytic transport in a Hull cell undergoing electroplating.

math.NA

Shifted HSS solvers for the indefinite Helmholtz equation

We provide an iterative solution approach for the indefinite Helmholtz equation discretised using finite elements, based upon a Hermitian Skew-Hermitian Splitting (HSS) iteration applied to the shifted operator, and prove that the iteration is k- and mesh-robust when O(k) HSS iterations are performed. The HSS iterations involve solving a shifted operator that is suitable for approximation by multigrid using standard smoothers and transfer operators, and hence we can use O(N) parallel processors in a high performance computing implementation, where N is the total number of degrees of freedom. We argue that the algorithm converges in O(k) wallclock time when within the range of scalability of the multigrid. We provide numerical results in both 2D and 3D verifying our proofs and demonstrating this claim, establishing a method that can make use of large scale high performance computing systems.

math.NA

Quasi-optimal complexity $hp$-FEM for the Poisson Equation on a rectangle

We show, in one dimension, that an $hp$-Finite Element Method ($hp$-FEM) discretisation can be solved in optimal complexity because the discretisation has a special sparsity structure that ensures that the reverse Cholesky factorisation (Cholesky starting from the bottom right instead of the top left) remains sparse. Moreover, computing and inverting the factorisation may parallelise across different elements. By incorporating this approach into an Alternating Direction Implicit (ADI) method \`a la Fortunato and Townsend (2020) we can solve, within a prescribed tolerance, an $hp$-FEM discretisation of the (screened) Poisson equation on a rectangle with quasi-optimal complexity: $O(N^2 \log N)$ operations where $N$ is the maximal total degrees of freedom in each dimension. When combined with fast Legendre transforms we can also solve nonlinear time-evolution partial differential equations in a quasi-optimal complexity of $O(N^2 \log^2 N)$ operations, which we demonstrate on the (viscid) Burgers' equation. We also demonstrate how the solver can be used as an effective preconditioner for PDEs with variable coefficients, including coefficients that support a singularity.

math.NA