In search of physical parameters influenced by flow patterns in a heterogeneous two-phase mixture in microchannels using concomitant measurements

2006 ◽  
Vol 32 (4) ◽  
pp. 483-498 ◽  
Author(s):  
Jerry K. Keska ◽  
William E. Simon
Keyword(s):  
Flow Patterns ◽  
Physical Parameters ◽  
Two Phase ◽  
Phase Mixture

Average Physical Parameters in an Air-Water Two-Phase Flow in a Small, Square-Sectioned Channel

1994 ◽  
Vol 116 (2) ◽  
pp. 247-254 ◽  
Author(s):  
J. K. Keska ◽  
R. D. Fernando
Keyword(s):  
Experimental Data ◽  
Flow Pattern ◽  
Two Phase Flow ◽  
Full Range ◽  
Flow Patterns ◽  
Physical Parameters ◽  
Phase Flow ◽  
Spatial Concentration ◽  
Two Phase ◽  
Concentration Measurements

This experimental study focuses on an adiabatic two-phase air-water flow generated in a small, horizontal, 6.35 mm square channel. Pressure and temperature were near standard conditions. Experimental data and correlations available in the literature, generally, do not consider the full range of concentration, small cross-sectional areas and direct physical parameters, such as concentration (void fraction) and/or phase velocities. Based on the direct measurement of in-situ spatial concentration (in a full range of concentrations, including gas and liquid phases only), and flow-pattern determination, the experimental data from the study are compared with data from the literature and with prediction by the generally accepted Lockhart-Martinelli’s and Chen’s models. Spatial concentration measurements were made with a computer-based system developed and built by the authors. Pressure drop over a length of the channel was also measured with pressure transducers. These measurements were made for a variety of flow conditions which encompassed bubble, slug, plug, and annular flow regimes. Flow patterns were established, and both mean and fluctuating components of the concentration measurements were used to objectively identify the flow patterns. These results, together with visual enhanced observation (stroboscope) supplemented with a high-speed CCD camera recording enhanced with dye injection, were used to obtain flow-pattern maps and compared with the literature. Spatial concentration is shown to be a key physical parameter in describing the state of the mixture in two-phase flow.

scholarly journals Machine Learning Model of Dimensionless Numbers to Predict Flow Patterns and Droplet Characteristics for Two-Phase Digital Flows

2021 ◽  
Vol 11 (9) ◽  
pp. 4251
Author(s):  
Jinsong Zhang ◽  
Shuai Zhang ◽  
Jianhua Zhang ◽  
Zhiliang Wang
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Digital Microfluidics ◽  
Flow Patterns ◽  
Machine Learning Algorithms ◽  
Dimensionless Numbers ◽  
Two Phase ◽  
The Difference ◽  
Input Variables ◽  
Digital Microfluidic

In the digital microfluidic experiments, the droplet characteristics and flow patterns are generally identified and predicted by the empirical methods, which are difficult to process a large amount of data mining. In addition, due to the existence of inevitable human invention, the inconsistent judgment standards make the comparison between different experiments cumbersome and almost impossible. In this paper, we tried to use machine learning to build algorithms that could automatically identify, judge, and predict flow patterns and droplet characteristics, so that the empirical judgment was transferred to be an intelligent process. The difference on the usual machine learning algorithms, a generalized variable system was introduced to describe the different geometry configurations of the digital microfluidics. Specifically, Buckingham’s theorem had been adopted to obtain multiple groups of dimensionless numbers as the input variables of machine learning algorithms. Through the verification of the algorithms, the SVM and BPNN algorithms had classified and predicted the different flow patterns and droplet characteristics (the length and frequency) successfully. By comparing with the primitive parameters system, the dimensionless numbers system was superior in the predictive capability. The traditional dimensionless numbers selected for the machine learning algorithms should have physical meanings strongly rather than mathematical meanings. The machine learning algorithms applying the dimensionless numbers had declined the dimensionality of the system and the amount of computation and not lose the information of primitive parameters.

scholarly journals Two-Phase Flow Mass Transfer Analysis of Airlift Pump for Aquaculture Applications

Fluids ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 226
Author(s):  
Rashal Abed ◽  
Mohamed M. Hussein ◽  
Wael H. Ahmed ◽  
Sherif Abdou
Keyword(s):  
Mass Transfer ◽  
Oxygen Transfer ◽  
Transfer Rate ◽  
Two Phase Flow ◽  
Oxygen Transfer Rate ◽  
Flow Patterns ◽  
Oxygen Mass Transfer ◽  
Phase Flow ◽  
Two Phase ◽  
Airlift Pump

Airlift pumps can be used in the aquaculture industry to provide aeration while concurrently moving water utilizing the dynamics of two-phase flow in the pump riser. The oxygen mass transfer that occurs from the injected compressed air to the water in the aquaculture systems can be experimentally investigated to determine the pump aeration capabilities. The objective of this study is to evaluate the effects of various airflow rates as well as the injection methods on the oxygen transfer rate within a dual injector airlift pump system. Experiments were conducted using an airlift pump connected to a vertical pump riser within a recirculating system. Both two-phase flow patterns and the void fraction measurements were used to evaluate the dissolved oxygen mass transfer mechanism through the airlift pump. A dissolved oxygen (DO) sensor was used to determine the DO levels within the airlift pumping system at different operating conditions required by the pump. Flow visualization imaging and particle image velocimetry (PIV) measurements were performed in order to better understand the effects of the two-phase flow patterns on the aeration performance. It was found that the radial injection method reached the saturation point faster at lower airflow rates, whereas the axial method performed better as the airflow rates were increased. The standard oxygen transfer rate (SOTR) and standard aeration efficiency (SAE) were calculated and were found to strongly depend on the injection method as well as the two-phase flow patterns in the pump riser.

Two-Phase Flow and Heat Transfer in Rectangular Micro-Channels

2003 ◽  
Author(s):  
Weilin Qu ◽  
Seok-Mann Yoon ◽  
Issam Mudawar
Keyword(s):  
Heat Transfer ◽  
Pressure Drop ◽  
Flow Pattern ◽  
Two Phase Flow ◽  
Flow Patterns ◽  
Heat Sinks ◽  
Phase Flow ◽  
Micro Channel ◽  
Two Phase ◽  
Micro Channels

Knowledge of flow pattern and flow pattern transitions is essential to the development of reliable predictive tools for pressure drop and heat transfer in two-phase micro-channel heat sinks. In the present study, experiments were conducted with adiabatic nitrogen-water two-phase flow in a rectangular micro-channel having a 0.406 × 2.032 mm cross-section. Superficial velocities of nitrogen and water ranged from 0.08 to 81.92 m/s and 0.04 to 10.24 m/s, respectively. Flow patterns were first identified using high-speed video imaging, and still photos were then taken for representative patterns. Results reveal that the dominant flow patterns are slug and annular, with bubbly flow occurring only occasionally; stratified and churn flow were never observed. A flow pattern map was constructed and compared with previous maps and predictions of flow pattern transition models. Annual flow is identified as the dominant flow pattern for conditions relevant to two-phase micro-channel heat sinks, and forms the basis for development of a theoretical model for both pressure drop and heat transfer in micro-channels. Features unique to two-phase micro-channel flow, such as laminar liquid and gas flows, smooth liquid-gas interface, and strong entrainment and deposition effects are incorporated into the model. The model shows good agreement with experimental data for water-cooled heat sinks.

scholarly journals Maximum Flow Rate of a Single Component, Two-Phase Mixture

1965 ◽  
Vol 87 (1) ◽  
pp. 134-141 ◽  
Author(s):  
F. J. Moody
Keyword(s):  
Flow Rate ◽  
Static Pressure ◽  
Maximum Flow ◽  
Single Component ◽  
Maximum Flow Rate ◽  
Vapor Flow ◽  
Two Phase ◽  
Slip Ratio ◽  
Phase Mixture ◽  
Local Slip

A theoretical model is developed for predicting the maximum flow rate of a single component, two-phase mixture. It is based upon annular flow, uniform linear velocities of each phase, and equilibrium between liquid and vapor. Flow rate is maximized with respect to local slip ratio and static pressure for known stagnation conditions. Graphs are presented giving maximum steam/water flow rates for: local static pressures between 25 and 3,000 psia, with local qualities from 0.01 to 1.00; local stagnation pressures and enthalpies which cover the range of saturation states.

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