论文标题
BICGSTAB的数值稳健，平行友好的变体，用于在平滑粒子流体动力学中粘性项的半平均整合
A numerically robust, parallel-friendly variant of BiCGSTAB for the semi-implicit integration of the viscous term in Smoothed Particle Hydrodynamics
论文作者
论文摘要
粘性项的隐式整合可以显着改善高粘性流体（如熔岩）的计算流体动力学性能。我们展示了对平滑颗粒流体动力学中半图像粘性整合的提议的改进，从而扩展了它以支持更广泛的边界模型。由于矩阵对称性的丢失，关键进步是双缀合物梯度稳定方法的更强大版本来求解线性系统，这也更适合在共享内存和分布式内存系统和分布式内存系统中并行化。新求解器的优点在具有牛顿和非牛顿流体的应用中被解释，涵盖了数值方面（由于使用更准确的边界模型的可能性而改善了收敛性）和计算方面（具有出色的强大规模和令人满意的弱缩放标度）。
Implicit integration of the viscous term can significantly improve performance in computational fluid dynamics for highly viscous fluids such as lava. We show improvements over our previous proposal for semi-implicit viscous integration in Smoothed Particle Hydrodynamics, extending it to support a wider range of boundary models. Due to the resulting loss of matrix symmetry, a key advancement is a more robust version of the biconjugate gradient stabilized method to solve the linear systems, that is also better suited for parallelization in both shared-memory and distributed-memory systems. The advantages of the new solver are demostrated in applications with both Newtonian and non-Newtonian fluids, covering both the numerical aspect (improved convergence thanks to the possibility to use more accurate boundary model) and the computing aspect (with excellent strong scaling and satisfactory weak scaling).
