基于复杂网络的气液两相流流型识别与动力学特性分析  

Flow pattern identification and dynamics characteristics analyses for gas-liquid two-phase flow in complex network

作　　者：孙庆明[1] 张博[1] 张海[2] 

机构地区：[1]大连理工大学能源与动力学院,辽宁大连116024 [2]温州市特种设备检测中心,浙江温州325000

出　　处：《大连理工大学学报》2015年第5期470-477,共8页Journal of Dalian University of Technology

基　　金：国家自然科学基金资助项目(51276025)

摘　　要：气液两相流作为一个非线性动力系统,其流动演化动力学特性尚未得到清楚的认识.以垂直上升管内空气-水两相流为研究对象,在通过流态模拟实验系统获取流态压差时间序列的基础上,构建流态复杂网络和流动演化复杂网络对气液两相流流型及其非线性动力学特性进行了研究.通过对流态复杂网络社团结构的分析获得了其社团结构与不同流型的对应关系,从而实现了对包括过渡流型在内的5种流型的辨识.通过对流动演化复杂网络分析发现,不同流型的流动演化复杂网络呈现出不同的社团结构,而且网络的信息熵演化趋势与流型转化过程密切相关,可以较好地揭示垂直上升管内气液两相流流态演化的动力学特性.As a nonlinear dynamic system,the flow evolution dynamics characteristics of gas-liquid two-phase flow are not clear.Air-water two-phase flow in vertical upward pipe is selected as the obj ect.Based on differential pressure time series measured from flow simulation experiment system, flow regime complex network（FRCN）and flow evolution complex network（FECN）are constructed to study gas-liquid two-phase flow pattern and its nonlinear dynamics characteristics.Through detecting the community structures of FRCN,the corresponding relations between community structures and flow patterns are obtained,consequently five flow patterns including transitional flow patterns are distinguished and identified.Through analyzing the FECN,it is found that the FECN of different flow patterns presents different community structures,and the evolutionary trend of FECN＇s network information entropy has close relation to the flow pattern transition,which can be employed to reveal the dynamics characteristics of gas-liquid two-phase flow evolution in vertical upward pipe.

关 键 词：气液两相流 流体动力学 时间序列 复杂网络 熵 

分 类 号：O359.1[理学—流体力学]