可压缩平滑粒子流体力学的自适应粒子细化

Rebecca Nealon, Daniel Price
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引用次数: 0

摘要

我们为可压缩平滑粒子流体力学(SPH)引入了自适应粒子细化。SPH 计算具有分辨率随质量变化的天然优势,但这并不总是最佳的。我们的实现方法允许用户指定可以更高分辨率的模拟局部区域。我们在实际应用中测试了我们的实现,包括一个环状圆盘、一颗嵌入圆盘的行星和一次飞越。通过与同类全局高分辨率计算的比较,我们发现我们的方法既准确又快速,在所显示的例子中,吸积到汇上的质量误差小于 9%,速度提高了 1.07-6.62 倍。我们的方法适应性强,易于扩展,例如,可以使用多个细化区域或取消细化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive particle refinement for compressible smoothed particle hydrodynamics
We introduce adaptive particle refinement for compressible smoothed particle hydrodynamics (SPH). SPH calculations have the natural advantage that resolution follows mass, but this is not always optimal. Our implementation allows the user to specify local regions of the simulation that can be more highly resolved. We test our implementation on practical applications including a circumbinary disc, a planet embedded in a disc and a flyby. By comparing with equivalent globally high resolution calculations we show that our method is accurate and fast, with errors in the mass accreted onto sinks of less than 9 percent and speed ups of 1.07-6.62 times for the examples shown. Our method is adaptable and easily extendable, for example with multiple refinement regions or derefinement.
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