Scalable angular adaptivity for Boltzmann transport
Scalable angular adaptivity for Boltzmann transport
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DOI：
10.1016/j.jcp.2019.109124
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发表时间：
2019-01
期刊：
影响因子：
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通讯作者：
S. Dargaville;A. Buchan;R. Smedley-Stevenson;Paul N. Smith;C. Pain
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文献类型：
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作者：
S. Dargaville;A. Buchan;R. Smedley-Stevenson;Paul N. Smith;C. Pain
本文描述了一个角度自适应算法的玻尔兹曼运输应用程序的第一次显示的证据O（n）的缩放在运行时间和内存使用，其中n是适应角度的数量。这种自适应性使用Haar小波，其执行建立在2D角域的分层P 0 FEM离散化之上的结构化h-自适应性，允许跨空间/能量应用不同的各向异性角分辨率。这些小波可以映射回其底层的P 0空间可缩放，允许传统的DG扫描算法，如果需要的话。相反，我们建立一个空间离散非结构化网格设计使用更少的内存比竞争的替代品在一般应用中，并构建一个兼容的矩阵自由多重网格方法，可以处理我们的适应角离散。固定的角度细化，沿着与定期和目标为基础的误差指标显示在三个例子中的问题，从中子学/辐射传输的应用。
This paper describes an angular adaptivity algorithm for Boltzmann transport applications which for the first time shows evidence of O (n) scaling in both runtime and memory usage, where n is the number of adapted angles. This adaptivity uses Haar wavelets, which perform structured h-adaptivity built on top of a hierarchical P 0 FEM discretisation of a 2D angular domain, allowing different anisotropic angular resolution to be applied across space/energy. These wavelets can be mapped back to their underlying P 0 space scalably, allowing traditional DG-sweep algorithms if desired. Instead we build a spatial discretisation on unstructured grids designed to use less memory than competing alternatives in general applications and construct a compatible matrix-free multigrid method which can handle our adapted angular discretisation. Fixed angular refinement, along with regular and goal-based error metrics are shown in three example problems taken from neutronics/radiative transfer applications.