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      Fast and accurate Voronoi density gridding from Lagrangian hydrodynamics data

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          Abstract

          Voronoi grids have been successfully used to represent density structures of gas in astronomical hydrodynamics simulations. While some codes are explicitly built around using a Voronoi grid, others, such as Smoothed Particle Hydrodynamics (SPH), use particle-based representations and can benefit from constructing a Voronoi grid for post-processing their output. So far, calculating the density of each Voronoi cell from SPH data has been done numerically, which is both slow and potentially inaccurate. This paper proposes an alternative analytic method, which is fast and accurate. We derive an expression for the integral of a cubic spline kernel over the volume of a Voronoi cell and link it to the density of the cell. Mass conservation is ensured rigorously by the procedure. The method can be applied more broadly to integrate a spherically symmetric polynomial function over the volume of a random polyhedron.

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          Most cited references 21

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          VORO++: a three-dimensional voronoi cell library in C++.

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            Computing the n-dimensional Delaunay tessellation with application to Voronoi polytopes

             D. Watson (1981)
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              Smoothed Particle Hydrodynamics and Magnetohydrodynamics

               Daniel Price (2010)
              This paper presents an overview and introduction to Smoothed Particle Hydrodynamics and Magnetohydrodynamics in theory and in practice. Firstly, we give a basic grounding in the fundamentals of SPH, showing how the equations of motion and energy can be self-consistently derived from the density estimate. We then show how to interpret these equations using the basic SPH interpolation formulae and highlight the subtle difference in approach between SPH and other particle methods. In doing so, we also critique several `urban myths' regarding SPH, in particular the idea that one can simply increase the `neighbour number' more slowly than the total number of particles in order to obtain convergence. We also discuss the origin of numerical instabilities such as the pairing and tensile instabilities. Finally, we give practical advice on how to resolve three of the main issues with SPMHD: removing the tensile instability, formulating dissipative terms for MHD shocks and enforcing the divergence constraint on the particles, and we give the current status of developments in this area. Accompanying the paper is the first public release of the NDSPMHD SPH code, a 1, 2 and 3 dimensional code designed as a testbed for SPH/SPMHD algorithms that can be used to test many of the ideas and used to run all of the numerical examples contained in the paper.
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                Author and article information

                Journal
                19 October 2017
                Article
                1710.07108

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                Custom metadata
                26 pages, 6 figures. For a sample implementation of the described algorithm, see https://github.com/mapetkova/kernel-integration
                astro-ph.IM astro-ph.CO astro-ph.EP astro-ph.GA astro-ph.SR

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