arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 1902.01458physics.flu-dyn
收藏

随机解决方案分析

Randomized resolvent analysis

Jean Hélder Marques Ribeiro, Chi-An Yeh, Kunihiko Taira

摘要:

对高雷诺数湍流进行全局预解式分析需要处理一个大的离散算子。尽管在分析中需要如此大的算子,但大多数预解式分析的应用仅提取少数主导预解式响应和强迫模式。在这里,我们考虑使用随机数值线性代数,以减少维数的预解算子实现计算速度和内存节省相比,标准的预解分析。为了实现这一目标,我们利用草图的线性算子与随机测试矩阵与高斯分布和从基流的见解纳入执行奇异值分解的低秩矩阵持有的主导特征的完整的预解算子。随机预解式分析的强度在翼型的湍流分离流上被证明。这种随机化方法为解决高雷诺数双全局和三全局基流的预解式分析扫清了道路。

英文摘要:

Performing global resolvent analysis for high-Reynolds-number turbulent flow calls for the handling of a large discrete operator. Even though such large operator is required in the analysis, most applications of resolvent analysis extracts only a few dominant resolvent response and forcing modes. Here, we consider the use of randomized numerical linear algebra to reduce the dimension of the resolvent operator for achieving computational speed up and memory saving compared to the standard resolvent analysis. To accomplish this goal, we utilize sketching of the linear operator with random test matrices with a Gaussian distribution and with insights from the base flow incorporated to perform singular value decomposition on a low-rank matrix holding dominant characteristics of the full resolvent operator. The strength of the randomized resolvent analysis is demonstrated on a turbulent separated flow over an airfoil. This randomized approach clears the path towards tackling resolvent analysis for higher-Reynolds number bi- and tri-global base flows.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑