p-Multigrid matrix-free discontinuous Galerkin solution strategies for the under-resolved simulation of incompressible turbulent flows
Matteo Franciolini, Lorenzo Botti, Alessandro Colombo, Andrea, Crivellini

TL;DR
This paper develops efficient, scalable p-multigrid matrix-free discontinuous Galerkin methods with Krylov smoothers for simulating incompressible turbulent flows, achieving significant memory and time savings.
Contribution
It introduces a novel p-multigrid preconditioner combining matrix-free and matrix-based smoothers, improving efficiency for large-scale turbulent flow simulations.
Findings
Achieved strong memory savings and faster execution times.
Validated methods on complex turbulent flow cases.
Demonstrated good agreement with experimental data.
Abstract
In recent years several research efforts focused on the development of high-order discontinuous Galerkin (dG) methods for scale resolving simulations of turbulent flows. Nevertheless, in the context of incompressible flow computations, the computational expense of solving large scale equation systems characterized by indefinite Jacobian matrices has often prevented from dealing with industrially-relevant computations. In this work we seek to improve the efficiency of Rosenbrock-type linearly-implicit Runge-Kutta methods by devising robust, scalable and memory-lean solution strategies. In particular, we introduce memory saving p-multigrid preconditioners coupling matrix-free and matrix-based Krylov iterative smoothers. The p-multigrid preconditioner relies on cheap block-diagonal smoother's preconditioners on the fine space to reduce assembly costs and memory allocation, and ensures an…
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