通过使用动态模式分解的空间电荷动态的减少顺序建模,加速粒子在细胞内动态等离子体模拟
Indranil Nayak1, Fernando L Teixeira1, Dong-Yeop Na2
1ElectroScience Laboratory and Department of Electrical and Computer Engineering, <a href="https://ror.org/00rs6vg23">The Ohio State University</a>, Columbus, Ohio 43212, USA.
Physical review. E
|July 18, 2024
概括
我们开发了一种数据驱动的方法,使用动态模式分解 (DMD) 在电磁粒子在细胞 (EMPIC) 等离子体模拟中模拟空间电荷动态,显著加速它们.
科学领域:
- 计算物理学的计算物理.
- 血物理学的等离子体物理学
- 数据驱动的建模.
背景情况:
- 动力等离子体模拟,如EMPIC模型带电粒子动力学.
- 这些动态对于理解等离子体行为至关重要,并且是计算密集的.
- 减少顺序模型提供了一条加速复杂模拟的途径.
研究的目的:
- 在EMPIC模拟中开发一个数据驱动的空间电荷动态的减少顺序模型.
- 为了利用动态模式分解 (DMD) 来建模等离子体电流密度演变.
- 加速EMPIC模拟,并实现新的分析和控制能力.
主要方法:
- 应用动态模式分解 (DMD) 来分析空间电荷动态.
- 使用低维特征空间建模了等离子体电流密度的时间演变.
- 将基于DMD的模型集成到EMPIC模拟中 (DMD-EMPIC方案).
主要成果:
- 证明了DMD在捕捉当前密度动态方面的有效性.
- 在使用DMD-EMPIC方案的EMPIC模拟中实现了显著的加速.
- 成功建模了包括电子束,虚拟阴极振荡和反向波振荡器在内的场景.
结论:
- DMD为EMPIC模拟提供了有效的减少顺序建模方法.
- 该DMD-EMPIC方案加速模拟,并有助于分析和控制.
- 这种数据驱动的方法提高了动力等离子体模拟的效率和适用性.
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