Nonlinear multi-scale dynamic stability of oil–gas–water three-phase flow in vertical upward pipe
Nonlinear multi-scale dynamic stability of oil–gas–water three-phase flow in vertical upward pipe
复制标题
垂直向上管道油气水三相流非线性多尺度动力稳定性
DOI：
10.1016/j.cej.2016.05.081
复制
发表时间：
2016-10
影响因子：
15.1
通讯作者：
Yi Tang
中科院分区：
文献类型：
--
作者：
Lian-Xin Zhuang;Ning-De Jin;An Zhao;Zhong-Ke Gao;Lu-Sheng Zhai;Yi Tang
表征油-水-气三相流的稳定性和非线性是一个非常重要的具有挑战性的问题。我们进行了实验并测量了带有八个电极的旋转电场电导传感器的波动信号。我们使用递推图和自适应最优核时频表示来从实验测量中识别不同的油-水-气三相流动模式。然后，我们采用多尺度加权复杂性熵因果平面（MS-WCECP）来探索五种典型油水气三相流结构的非线性特征。结果表明我们的方法能够指示流型转变。特别是，随着尺度的增加，将会丢失更多的信息。段塞流最终处于混沌区域，复杂性较高；搅动流从混沌区域下降到随机噪声区域，表明稳定性下降；而气泡流的下降程度最大，说明气泡流的随机性最强。这些发现表明，多尺度加权复杂性熵因果平面可以有效地描述三相流结构的转变，并可作为探测三相流非线性动力学的有用工具。
Characterizing stability and nonlinearity underlying oil–water–gas three-phase flow is a challenging problem of significant importance. We carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We use recurrence plot and adaptive optimal kernel time–frequency representation to recognize different oil–water–gas three-phase flow patterns from experimental measurements. Then we employ multi-scale weighted complexity entropy causality plane (MS-WCECP) to explore the nonlinear characteristics for five typical oil–water–gas three-phase flow structures. The results suggest that our method enables to indicate flow pattern transitions. In particular, with the increase of scales, more information will be lost. Slug flow ends up in chaotic region, representing high complexity; Churn flow falls down from the chaotic to the random noise area, indicating the decreasing stability; while the drop degree of bubble flow is the biggest, suggesting that bubble flow has the most randomness. These findings demonstrate that multi-scale weighted complexity entropy causality plane can effectively depict the transitions of three-phase flow structures and serve as a useful tool for probing the nonlinear dynamics of the three-phase flows.
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影响因子：
2.6
作者：
Martin, MT;Plastino, A;Rosso, OA
通讯作者：
Rosso, OA
影响因子：
15.1
作者：
Biswas, Koushik Guha;Patra, Rahul;Basu, Jayanta Kumar
通讯作者：
Basu, Jayanta Kumar
DOI：
10.1073/pnas.0806082105
发表时间：
2008-12-16
影响因子：
11.1
作者：
Xu, Xiaoke;Zhang, Jie;Small, Michael
通讯作者：
Small, Michael
影响因子：
5.4
作者：
JONES, DL;BARANIUK, RG
通讯作者：
BARANIUK, RG
DOI：
10.1016/j.physa.2010.01.007
发表时间：
2010-05
影响因子：
3.3
作者：
L. Zunino;Massimiliano Zanin;B. Tabak;D. Pérez;O. Rosso
通讯作者：
L. Zunino;Massimiliano Zanin;B. Tabak;D. Pérez;O. Rosso