论文标题
大规模平行的拉格朗日粒子代码和应用
Massively-Parallel Lagrangian Particle Code and Applications
论文作者
论文摘要
拉格朗日粒子流体动力学方法的大量平行，分布式内存算法[R. Samulyak，X。Wang，H.-C。 Chen，Lagrangian粒子方法用于可压缩流体动力学，J。Comput。 Phys。，362（2018），1-19]已经开发，验证和实施。并行算法的关键组成部分是一个粒子管理模块，其中包括OCTREE数据库的并行结构，动态适应和OCTREES的细化以及粒子在平行子域之间的迁移。粒子管理模块基于P4est（K-Trees的平行森林）库。大规模平行的拉格朗日粒子代码已应用于各种基本科学和应用问题。还提出了向热核融合设备注入杂质的拉格朗日粒子代码应用的摘要，并介绍了超音速氢射流的仿真，以支持激光 - 播种Wakefield加速项目。
Massively-parallel, distributed-memory algorithms for the Lagrangian particle hydrodynamic method [R. Samulyak, X. Wang, H.-C. Chen, Lagrangian particle method for compressible fluid dynamics, J. Comput. Phys., 362 (2018), 1-19] have been developed, verified, and implemented. The key component of parallel algorithms is a particle management module that includes a parallel construction of octree databases, dynamic adaptation and refinement of octrees, and particle migration between parallel subdomains. The particle management module is based on the p4est (parallel forest of k-trees) library. The massively-parallel Lagrangian particle code has been applied to a variety of fundamental science and applied problems. A summary of Lagrangian particle code applications to the injection of impurities into thermonuclear fusion devices and to the simulation of supersonic hydrogen jets in support of laser-plasma wakefield acceleration projects has also been presented.
