SPHS: Smoothed Particle Hydrodynamics with a higher order dissipation switch
SPHS: Smoothed Particle Hydrodynamics with a higher order dissipation switch
复制标题
DOI：
10.1111/j.1365-2966.2012.20819.x
复制
发表时间：
2011-11
影响因子：
4.8
通讯作者：
Justin I. Read;Justin I. Read;T. Hayfield;T. Hayfield
中科院分区：
文献类型：
--
作者：
Justin I. Read;Justin I. Read;T. Hayfield;T. Hayfield
我们提出了一种平滑粒子流体动力学的新颖实现，它使用速度散度的空间导数作为高阶耗散开关。我们的开关（二阶精度）可以在流量收敛发生之前进行检测。如果粒子轨迹要交叉，我们会打开通常的 SPH 人工粘度，以及所有平流流体量（例如熵）中的保守耗散。粘度和耗散项（数值误差）旨在确保当粒子彼此接近时所有流体量保持单一值，遵守守恒定律，并随着分辨率的增加在给定的物理尺度上消失。 SPHS 缓解了“经典”SPH 的许多已知问题，成功解决了混合问题，并随着分辨率的提高恢复了数值收敛。另一个关键优势是，以与熵类似的方式处理粒子质量，我们能够使用多质量粒子，从而显着改善对细化策略的控制。我们提供了广泛的代码测试，包括 Sod 激波管、Sedov-Taylor 爆炸波、开尔文-亥姆霍兹不稳定性、“斑点测试”和一些收敛测试。我们的方法在所有测试中都表现良好，与分析预期非常吻合。
We present a novel implementation of smoothed particle hydrodynamics that uses the spatial derivative of the velocity divergence as a higher order dissipation switch. Our switch – which is second order accurate – detects flow convergence before it occurs. If particle trajectories are going to cross, we switch on the usual SPH artificial viscosity, as well as conservative dissipation in all advected fluid quantities (e.g. the entropy). The viscosity and dissipation terms (that are numerical errors) are designed to ensure that all fluid quantities remain single valued as particles approach one another, to respect conservation laws, and to vanish on a given physical scale as the resolution is increased. SPHS alleviates a number of known problems with ‘classic’ SPH, successfully resolving mixing, and recovering numerical convergence with increasing resolution. An additional key advantage is that – treating the particle mass similarly to the entropy – we are able to use multimass particles, giving significantly improved control over the refinement strategy. We present a wide range of code tests including the Sod shock tube, Sedov–Taylor blast wave, Kelvin–Helmholtz Instability, the ‘blob test’ and some convergence tests. Our method performs well on all tests, giving good agreement with analytic expectations.