78 research outputs found

    AIR multigrid with GMRES polynomials (AIRG) and additive preconditioners for Boltzmann transport

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    We develop a reduction multigrid based on approximate ideal restriction (AIR) for use with asymmetric linear systems. We use fixed-order GMRES polynomials to approximate Aff−1A_\textrm{ff}^{-1} and we use these polynomials to build grid transfer operators and perform F-point smoothing. We can also apply a fixed sparsity to these polynomials to prevent fill-in. When applied in the streaming limit of the Boltzmann Transport Equation (BTE), with a P0^0 angular discretisation and a low-memory spatial discretisation on unstructured grids, this "AIRG" multigrid used as a preconditioner to an outer GMRES iteration outperforms the lAIR implementation in hypre, with two to three times less work. AIRG is very close to scalable; we find either fixed work in the solve with slight growth in the setup, or slight growth in the solve with fixed work in the setup when using fixed sparsity. Using fixed sparsity we see less than 20% growth in the work of the solve with either 6 levels of spatial refinement or 3 levels of angular refinement. In problems with scattering AIRG performs as well as lAIR, but using the full matrix with scattering is not scalable. We then present an iterative method designed for use with scattering which uses the additive combination of two fixed-sparsity preconditioners applied to the angular flux; a single AIRG V-cycle on the streaming/removal operator and a DSA method with a CG FEM. We find with space or angle refinement our iterative method is very close to scalable with fixed memory use

    Fokker-Planck-Based Acceleration for SN Equations with Highly Forward Peaked Scattering in Slab Geometry

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    Short mean free paths are characteristic of charged particles. High energy charged particles often have highly forward peaked scattering cross sections. Transport problems involving such charged particles are also highly optically thick. When problems simultaneously have forward peaked scattering and high optical thickness, their solution, using standard iterative methods, becomes very inefficient. In this dissertation, we explore Fokker-Planck-based acceleration for solving such problems

    Scalable angular adaptivity for Boltzmann transport

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    This paper describes an angular adaptivity algorithm for Boltzmann transport applications which for the first time shows evidence of O(n)\mathcal{O}(n) scaling in both runtime and memory usage, where nn is the number of adapted angles. This adaptivity uses Haar wavelets, which perform structured hh-adaptivity built on top of a hierarchical P0_0 FEM discretisation of a 2D angular domain, allowing different anisotropic angular resolution to be applied across space/energy. Fixed angular refinement, along with regular and goal-based error metrics are shown in three example problems taken from neutronics/radiative transfer applications. We use a spatial discretisation designed to use less memory than competing alternatives in general applications and gives us the flexibility to use a matrix-free multgrid method as our iterative method. This relies on scalable matrix-vector products using Fast Wavelet Transforms and allows the use of traditional sweep algorithms if desired
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