Identificacion Principal del registro INGC-EBK-000628

Control Number Identifier AR-LpUFI

LAST MODIFICATION DATE 20160913123907

CONTROL FIELD cr nn 008mamaa

CONTROL FIELD 131226s2014 gw | s |||| 0|eng d

a International Standard Book Number 9783642383731

a Standard number or code 10.1007/978-3-642-38373-1

a Personal name Gao, Zhong-Ke.

a Title Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks

h Medium [libro electrónico] /

c Statement of responsibility, etc by Zhong-Ke Gao, Ning-De Jin, Wen-Xu Wang.

a Place of publication, distribution, etc Berlin, Heidelberg :

b Name of publisher, distributor, etc Springer Berlin Heidelberg :

b Name of publisher, distributor, etc Imprint: Springer,

c Date of publication, distribution, etc 2014.

a Extent xiii, 103 p. :

b Other physical details il.

a Series statement SpringerBriefs in Applied Sciences and Technology,

x International Standard Serial Number 2191-530X

a Formatted contents note Introduction -- Definition of flow patterns -- The experimental flow loop facility and data acquisition -- Community detection in flow pattern complex network -- Nonlinear dynamics in fluid dynamic complex network -- Gas-water fluid structure complex network -- Oil-water fluid structure complex network -- Directed weighted complex network for characterizing gas-liquid slug flow -- Markov transition probability-based network for characterizing horizontal gas-liquid two-phase flow -- Recurrence network for characterizing bubbly oil-in-water flows -- Conclusions. .

a Summary, etc Understanding the dynamics of multi-phase flows has been a challenge in the fields of nonlinear dynamics and fluid mechanics. This chapter reviews our work on two-phase flow dynamics in combination with complex network theory. We systematically carried out gas-water/oil-water two-phase flow experiments for measuring the time series of flow signals which is studied in terms of the mapping from time series to complex networks. Three network mapping methods were proposed for the analysis and identification of flow patterns, i.e. Flow Pattern Complex Network (FPCN), Fluid Dynamic Complex Network (FDCN) and Fluid Structure Complex Network (FSCN). Through detecting the community structure of FPCN based on K-means clustering, distinct flow patterns can be successfully distinguished and identified. A number of FDCNâ_Ts under different flow conditions were constructed in order to reveal the dynamical characteristics of two-phase flows. The FDCNs exhibit universal power-law degree distributions. The power-law exponent and the network information entropy are sensitive to the transition among different flow patterns, which can be used to characterize nonlinear dynamics of the two-phase flow. FSCNs were constructed in the phase space through a general approach that we introduced. The statistical properties of FSCN can provide quantitative insight into the fluid structure of two-phase flow. These interesting and significant findings suggest that complex networks can be a potentially powerful tool for uncovering the nonlinear dynamics of two-phase flows.

a Topical term or geographic name as entry element Chemical engineering.

a Topical term or geographic name as entry element Amorphous substances.

a Topical term or geographic name as entry element Complex fluids.

a Topical term or geographic name as entry element Phase transitions (Statistical physics).

a Topical term or geographic name as entry element Physical measurements.

a Topical term or geographic name as entry element Measurement.

a Topical term or geographic name as entry element Fluid mechanics.

a Topical term or geographic name as entry element Engineering.

a Topical term or geographic name as entry element Industrial Chemistry

a Topical term or geographic name as entry element Phase Transitions and Multiphase Systems.

a Topical term or geographic name as entry element Measurement Science and Instrumentation.

a Topical term or geographic name as entry element Soft and Granular Matter, Complex Fluids and Microfluidics.

a Personal name Jin, Ning-De.

a Personal name Wang, Wen-Xu.

u Uniform Resource Identifier (R) http://dx.doi.org/10.1007/978-3-642-38373-1

c item type EBK

a descripción COM