In the field of fluid mechanics, it is a potential consensus that nonlinear dimensionality
reduction (DR) techniques outperform linear methods. However, this conclusion has been …

Cavitation is a quasi-periodic process, and its non-stationarity leads to increasingly complex
flow field structures. On the other hand, characterizing the flow field with greater precision …

This study explores challenges in multivariate modal decomposition for various flow
scenarios, emphasizing the problem of inconsistent physical modes in Proper Orthogonal …

The rapid and accurate recognition of cavitation in centrifugal pumps has become essential
for improving production efficiency and ensuring machinery longevity. To address the …

Modal decomposition is a data-driven method widely used in fluid mechanics to extract
energy and dynamically significant features of fluid flow. However, traditional modal …

High-precision numerical simulation for solving unsteady flow fields is both time-and labor-
intensive. Additionally, it is challenging to directly apply to multidisciplinary design fields …

The application of data-driven methods to study cavitation flow provides insights into the
underlying mechanisms and richer physical details of cavitation phenomena. This paper …

The Earth's outer core dynamics involve convective fluid motion generating an observable
geomagnetic field. The velocity and magnetic fields exhibit characteristic spatiotemporal …

This paper introduces temporal information shared multi-variable dynamic mode
decomposition (TIMDMD), a novel data-driven algorithm for multi-variable modal …

重点探讨了在低雷诺数和大攻角条件下, 俯仰翼型复杂流体流动的非线性动力学特性.
研究通过整合多个相互关联的变量, 利用主成分分析(principal component analysis, PCA) …