Dynamic mode decomposition for data-driven modeling of free surface sloshing

被引:1
|
作者
Zhao, Xielin [1 ,2 ]
Guo, Ruiwen [1 ,2 ]
Yu, Xiaofei [3 ]
Huang, Qian [3 ]
Feng, Zhipeng [3 ]
Zhou, Jinxiong [1 ,2 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Strength & Vibrat Mech Struct, Xian 710049, Peoples R China
[2] Xi An Jiao Tong Univ, Sch Aerosp, Xian 710049, Peoples R China
[3] Nucl Power Inst China, Key Lab Nucl Reactor Syst Design Technol, Chengdu 610200, Peoples R China
来源
MODERN PHYSICS LETTERS B | 2022年 / 36卷 / 19期
基金
中国国家自然科学基金;
关键词
Dynamic mode decomposition; sloshing; free surface; data-driven; reduced-order modeling; SPECTRAL PROPERTIES; FINITE-ELEMENT; FLUID-FLOWS; VOF METHOD; SIMULATION; SYSTEMS; VOLUME;
D O I
10.1142/S0217984922500361
中图分类号
O59 [应用物理学];
学科分类号
摘要
The recently emerged data-driven dynamic mode decomposition (DMD) method was employed to investigate the free surface sloshing dynamics of a partially filled rigid tank excited by horizontal harmonic motions. The volume of fluid algorithm was adopted for liquid-gas free surface tracking, and DMD was utilized for decomposition with physical interpretations of the DMD modes and the eigenvalues. Our results demonstrate that DMD works well for both data reconstruction and future-state prediction in terms of either free surface profiles or the sloshing pressure exerted on the rigid wall. DMD presents an efficient and versatile approach for accelerated reduced-order modeling and future-state forecasting. Our efforts provide the first reference on use of DMD for free surface sloshing problems to the best knowledge of the authors. We publicly share our data and codes for all the implementation.
引用
收藏
页数:12
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