Evolution of High-Viscosity Gas–Liquid Flows as Viewed Through a Detrended Fluctuation Characterization

Hernández, Jesús Hernández; Galaviz, D.; Torres, Lizeth; Palacio-Pérez, Arturo; Rodríguez-Valdés, A.; Vicente, W.

doi:10.3390/pr7110822

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…Hernández et al [17] characterize the high viscosity gas-liquid intermittent flows by detrended fluctuation analysis. Specifically, the authors investigated the long-term evolution of highly viscous two-phase pipe flows of glycerin/air blends.…”

Section: Papers Presented In the Special Issuementioning

confidence: 99%

Recent Advances on Optimization for Control, Observation, and Safety

2020

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Section: Papers Presented In the Special Issuementioning

confidence: 99%

Recent Advances on Optimization for Control, Observation, and Safety

2020

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“…In this regard, Zhai et al presented the fractal scales for various flow patterns by using DFA to study gas-liquid twophase flow [24]. Hernández et al discovered that the multifractal DFA method enabled the accurate recognition of the distinct energy levels present in the gas-liquid two-phase flow, in accordance with the observed flow patterns at different locations [25]. There have been two notable developments in DFA over the past few decades.…”

Section: Introductionmentioning

confidence: 99%

Multifractal magnitude and sign correlations in multiphase flows

Ren,

Jin

2024

Meas. Sci. Technol.

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It is important to reveal the complex phenomenon of bubble coalescence or breakup in gas-liquid two-phase flow to understand the dynamic mechanism of flow pattern transition. Magnitude and sign decomposition pave a way to study the linear and nonlinear fractal characteristic separately. In this work, we extend this method to multifractal analysis, namely the multifractal magnitude and sign correlations. Test was conducted and an eight-electrode rotating conductivity sensor is utilized to collect the signals of different flow patterns in the gas-liquid two phase flow. The signal is initially decomposed into magnitude time series and sign time series. The width and difference of multifractal spectrums are introduced to characterize the nonlinear dynamics in the flow pattern evolution that gas-liquid two-phase slug flow breaks into the bubble flow or loses stability transforms into churn flow. And then these two parameters of multifractal magnitude and sign decomposition are fed into k-Nearest Neighbor for flow pattern identification. The results suggest that multifractal magnitude and sign decomposition has higher prediction accuracy (93%) than traditional multifractal analysis. The findings show that multifractal magnitude and sign correlations analysis is a powerful technique for investigating the flow dynamic of gas-liquid two phase flow.

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“…Dini and Asadi [12] designed a methodology based on particle swarm optimization (PSO) to identify the PRV that requires adjustment and obtain pressure management in the system; the network model was designed in EPANET. Hernández et al [13] proposed a detrended fluctuation analysis (or DFA) to highlight some of the traits such as the head loss of high-viscosity gas-liquid flows. Navarro et al [14] designed a leak diagnosis system for a pipeline and residue analysis using genetic algorithms (GA) to minimize location error.…”

Section: Introductionmentioning

confidence: 99%

Predictive Control in Water Distribution Systems for Leak Reduction and Pressure Management via a Pressure Reducing Valve

et al. 2022

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This work proposes a model predictive control (MPC) strategy for pressure management and leakage reduction in a water distribution system (WDS). Unlike most of the reported models that mainly consider EPANET-based models, the proposed method considers its dynamic representation given by ordinary differential equations. The proposed MPC uses a pressure-reducing valve (PRV) as a control element to regulate the pressure in the WDS to track the demand. The control scheme proposes a strategy to manage the high nonlinearity of the PRV and takes into account the demand profile throughout the day as well as the leaks that occur in the pipeline. The estimates of magnitude and location of the leak are provided by an Extended Kalman Filter from previous work and with the aid of a rule-based set point manager reduces the fluid loss in the event of a leak. Different scenarios are studied to illustrate the effectiveness of the proposed control system, achieving an approximate reduction of up to 5% of water losses, demonstrating robustness in the case of uncertainty in the leak location estimate.

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Evolution of High-Viscosity Gas–Liquid Flows as Viewed Through a Detrended Fluctuation Characterization

Cited by 7 publications

References 24 publications

Recent Advances on Optimization for Control, Observation, and Safety

Recent Advances on Optimization for Control, Observation, and Safety

Multifractal magnitude and sign correlations in multiphase flows

Predictive Control in Water Distribution Systems for Leak Reduction and Pressure Management via a Pressure Reducing Valve

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