標(biāo)題: Titlebook: Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks; Zhong-Ke Gao,Ning-De Jin,Wen-Xu Wang Book 2014 The Author(s) [打印本頁] 作者: 初生 時間: 2025-3-21 20:01
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks影響因子(影響力)
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks影響因子(影響力)學(xué)科排名
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks網(wǎng)絡(luò)公開度
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks被引頻次
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks被引頻次學(xué)科排名
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks年度引用
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks年度引用學(xué)科排名
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks讀者反饋
書目名稱Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks讀者反饋學(xué)科排名
作者: judicial 時間: 2025-3-21 21:35 作者: 推延 時間: 2025-3-22 03:20 作者: Acupressure 時間: 2025-3-22 08:00
Nonlinear Analysis of Gas-Water/Oil-Water Two-Phase Flow in Complex Networks978-3-642-38373-1Series ISSN 2191-530X Series E-ISSN 2191-5318 作者: 輕打 時間: 2025-3-22 11:52 作者: 錫箔紙 時間: 2025-3-22 14:47 作者: 挖掘 時間: 2025-3-22 17:50
Nonlinear Dynamics in Fluid Dynamic Complex Network,To gain insight into the nonlinear dynamics of gas-water two-phase flow, we construct Fluid Dynamic Complex Network (FDCN) from one conductance fluctuating signal.作者: 植物茂盛 時間: 2025-3-22 22:46
Gas-Water Fluid Structure Complex Network,In general, the traditional nonlinear time series analysis methods (chaotic attractor morphology, complexity measures and chaotic recurrence plot) cannot effectively reveal the complex fluid structure of two-phase flow.作者: 損壞 時間: 2025-3-23 04:47
Oil-Water Fluid Structure Complex Network,Due to the interplay among many complex factors such as liquid-liquid phase interfacial interaction and the existence of a gravitational component normal to the flow direction, an inclined oil-water flow exhibits highly irregular, random, and unsteady flow structure as compared with a vertical two-phase flow.作者: Phagocytes 時間: 2025-3-23 06:51 作者: obnoxious 時間: 2025-3-23 10:15 作者: MOCK 時間: 2025-3-23 15:22 作者: 骯臟 時間: 2025-3-23 18:28 作者: 內(nèi)行 時間: 2025-3-23 22:17 作者: Aspiration 時間: 2025-3-24 04:52 作者: Retrieval 時間: 2025-3-24 10:11
Recurrence Network for Characterizing Bubbly Oil-in-Water Flows,nd obtained results as follows: Mapping a time series into a complex network allows quantitatively characterizing the structural characteristics of complex systems that are composed of a large numbers of entities interacting with each other in a complex manner.作者: 受人支配 時間: 2025-3-24 11:26 作者: Dictation 時間: 2025-3-24 18:14
Community Detection in Flow Pattern Complex Network,epresented by a single node and the edge is determined by the strength of correlation between nodes. Flow condition refers to the flow behavior under different proportions of gas flow rate and water flow rate in the pipe. Since we configured 90 different proportions of gas flow rate and water flow r作者: synovium 時間: 2025-3-24 20:18
Markov Transition Probability-Based Network for Characterizing Horizontal Gas-Liquid Two-Phase Flowhase flow [.]. We here introduce methodology and obtained results as follows: A Markov chain is a mathematical system that undergoes transitions from one state to another, between a finite or countable number of possible states.作者: Dictation 時間: 2025-3-25 00:15 作者: anthesis 時間: 2025-3-25 06:26
2191-530X m experimental time series signals are provided.UnderstandinUnderstanding 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 systematic作者: 外面 時間: 2025-3-25 07:44
Community Detection in Flow Pattern Complex Network,ate to obtain 90 conductance fluctuating signals in the gas-water two-phase flow experiment, there are 90 different flow conditions (i.e., the number of nodes contained in FPCN is 90), in which each node corresponds to one of these 90 conductance fluctuating signals.作者: Obstruction 時間: 2025-3-25 12:37 作者: 歡騰 時間: 2025-3-25 18:02
Book 2014 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作者: MARS 時間: 2025-3-25 22:12
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