当前位置: X-MOL 学术Phys. Lett. A › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Topological causality analysis of horizontal gas-liquid flows based on cross map of phase spaces
Physics Letters A ( IF 2.6 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.physleta.2020.126693
Lusheng Zhai , Jie Yang

Abstract Nonlinear systems are always characterized by the interactions between constituents which yield data in the form of time series. Exploration of the causality between the times series is beneficial for understanding the dynamics of the system. We introduce a topological causality method to explore the dynamics of horizontal gas-liquid flows. First, the principle of the topological causality algorithm is illustrated and validated using the Lorenz system and transfer entropy. Then, we conducted an experiment of gas-liquid flows in a horizontal pipe, during which a wire-mesh sensor (WMS) was used to capture the flow structures. The WMS data at different time frames are embedded in high-dimension phase spaces. Through building a cross map between coupled phase spaces, a cross map smoothness was employed to derive the topological causality index. The causality index enables us to understand the mechanism of the flow pattern transition and the intrinsic dynamics of the transient gas-liquid flows.

中文翻译:

基于相空间交叉图的气液水平流动拓扑因果关系分析

摘要 非线性系统总是以成分之间的相互作用为特征,这些成分以时间序列的形式产生数据。探索时间序列之间的因果关系有利于理解系统的动力学。我们引入了一种拓扑因果关系方法来探索水平气液流动的动力学。首先,使用洛伦兹系统和传递熵来说明和验证拓扑因果关系算法的原理。然后,我们进行了水平管道中气液流动的实验,在此期间使用丝网传感器(WMS)来捕获流动结构。不同时间帧的 WMS 数据嵌入在高维相空间中。通过建立耦合相空间之间的交叉映射,使用交叉图平滑度来推导拓扑因果关系指数。因果关系指数使我们能够了解流型转变的机制和瞬态气液流动的内在动力学。
更新日期:2020-09-01
down
wechat
bug