适应式笛卡尔网格的平行方法,用于可压缩流体模拟
Xinyu Qi1, Yuchen Yang1, Linlin Tian1
1College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016 China.
概括
本研究介绍了一种高效的笛卡尔网格生成和幽灵细胞方法 (GCM),用于模拟复杂的流体流. 该方法提高了可压缩流体模拟的并行可扩展性,包括冲击和不稳定动力学.
科学领域:
- 计算流体动力学的流体动力学.
- 数字分析 数字分析
背景情况:
- 具有自适应网状精细化 (AMR) 的卡特西亚格子对复杂的几何形状和流量有效.
- 现有的基于Cartesian的AMR库在模拟对象周围的流动方面存在局限性.
研究的目的:
- 开发一种高效的卡特西亚格子生成方法和墙壁边界信息传输方法.
- 为了平行化幽灵细胞方法 (GCM) 以提高模拟能力.
- 为平行框架适应多价值幽灵细胞方法.
主要方法:
- 实施一个高效的卡特西安网格生成技术.
- 开发用于并行GCM的墙壁边界信息传输方法.
- 适应多值幽灵细胞方法进行并行处理.
- 与开源的p4est库集成,用于自动压缩流模拟.
主要成果:
- 实现了可压缩流量的自动和高效的模拟.
- 证明了各种流型的可接受能力和并行可扩展性.
- 成功处理了涉及冲击波,,多体相互作用和不稳定的现象的流动.
结论:
- 拟议的数值方法对于模拟复杂的可压缩流程是有效的.
- 该方法表现出强大的并行可扩展性,适合要求高的计算任务.
- 根据参考数据进行验证,证实各种流量模式的准确性.
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