Model of bubble velocity vector measurement in upward and downward bubbly two-phase flows using a four-sensor optical probe

Tian, Daogui; Yan, Changqi; Sun, Licheng

doi:10.1016/j.pnucene.2014.08.005

Cited by 17 publications

(17 citation statements)

References 35 publications

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“…The deviation of 10% between the voltage wave width of sensor 4 and other three responding voltage waves width is small enough to select related signals. Detailed information for the signal processing were described by Yang, Xie, and Tian

\begin{matrix} 0.9 < \frac{2 Δ t_{0}}{Δ t_{0} + (Δ t_{1 b} - Δ t_{1 a})} < 1.1 \\ 0.9 < \frac{2 Δ t_{0}}{Δ t_{0} + (Δ t_{2 b} - Δ t_{2 a})} < 1.1 \\ 0.9 < \frac{2 Δ t_{0}}{Δ t_{0} + (Δ t_{3 b} - Δ t_{3 a})} < 1.1 \end{matrix}

…”

Section: Experiments and Materialsmentioning

confidence: 99%

A study on hydrodynamic characteristics in a Φ38 pulsed extraction column by four‐sensor optical fiber probe

Yuan

Gao

2016

AIChE Journal

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Accurate prediction of dispersed phase droplet behavior is crucial to the design and scaling‐up of an extraction column. In this article, the dispersed droplet velocity algorithm and the diameter algorithm in a liquid–liquid two‐phase flow have been developed based on the bubble velocity model in gas–liquid two‐phase flow of Lucas [Measurement Science & Technology. 749, 758(2005)] and Shen [International Journal of Multiphase Flow. 593, 617(2005)]. Hydrodynamic characteristics, including droplet diameter, holdup and droplet velocity, were measured using a self‐made four‐sensor optical fiber probe in a 38 mm‐diameter pulsed sieve‐plate extraction column. Water and kerosene were used as continuous and dispersed phases, respectively. The influences of the pulsed intensity, the continuous and dispersed phase superficial velocities on the hydrodynamic characteristics were investigated. The experimental results show that it is reliable to use a four‐sensor optical probe to measure the hydrodynamic characteristics of a pulsed extraction column. © 2016 American Institute of Chemical Engineers AIChE J, 63: 801–811, 2017

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\begin{matrix} 0.9 < \frac{2 Δ t_{0}}{Δ t_{0} + (Δ t_{1 b} - Δ t_{1 a})} < 1.1 \\ 0.9 < \frac{2 Δ t_{0}}{Δ t_{0} + (Δ t_{2 b} - Δ t_{2 a})} < 1.1 \\ 0.9 < \frac{2 Δ t_{0}}{Δ t_{0} + (Δ t_{3 b} - Δ t_{3 a})} < 1.1 \end{matrix}

…”

Section: Experiments and Materialsmentioning

confidence: 99%

A study on hydrodynamic characteristics in a Φ38 pulsed extraction column by four‐sensor optical fiber probe

Yuan

Gao

2016

AIChE Journal

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“…In 2015, Tian et al created a model for bubble velocity in upward and downward bubbly flows by using a four-sensor optical probe. The comparison between the area-averaged VF and bubble velocity was within 15% under various conditions for the optical sensor compared to the photographic method (Tian et al, 2015). These tests demonstrated the reliability of the optical probe while measuring a variety of two-phase conditions.…”

Section: Optical Probesmentioning

confidence: 67%

Comparison of data processing algorithm performance for optical and conductivity void probes

Mills

Schlegel

2019

Exp. Comput. Multiph. Flow

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In commercial nuclear reactors, heat exchangers, and bubble column reactors, two-phase flows are present. When predicting the safety and process efficiency of these systems, it is necessary to model the behavior found in them. The most common model used in two-phase flows is the two-fluid model due to its practicality. In the two-fluid model, two key parameters are the void fraction (VF, also known as the gas fraction or gas holdup) and interfacial area concentration (IAC, also known as interfacial area density). In order to produce accurate results, the bubbles are separated into groups based on the transport properties. When benchmarking models, experimental data are required. In many cases the experimental data are produced with the use of intrusive conductivity or optical probes. Recently a new data processing algorithm was developed to improve bubble interface identification and implement a method to group bubbles based on diameter rather than chord length. In this paper, the new data processing algorithm is evaluated by comparing the results when using both conductivity and optical probes. At a data acquisition frequency of 22 kHz, the optical probe collected more bubbles than the conductivity probe using the old algorithm. The new algorithm results in similar bubble counts for both instruments. There is a shift in bubbles from Group 1 to Group 2 in both the optical and conductivity probes. The new bubble size calculation means that several bubbles, which were previously classified as "spherical/distorted", are now classified as "cap/slug/churn" bubbles for both the optical and conductivity probes. However due to low sample rates used in this research, the IAC is larger for the conductivity probe when compared to the optical probe by 10% to 60%. While some of these changes were expected, the increase in the IAC was larger than the reported uncertainty of the instruments.

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“…(2) The bubble velocity measurement errors of both the traditional ground measuring devices and the designed bubble sensor are basically within ±5%, and their bubble velocity measurement errors therefore are the same [ 30 , 31 , 32 ]. The bubble volume measurement error of the designed bubble sensor is ±7%, which is slightly larger than that of traditional ground measuring devices [ 33 , 34 ], but the designed bubble sensor nevertheless can meet the requirements of field use.…”

Section: Discussionmentioning

confidence: 99%

Research on the Conductivity-Based Detection Principles of Bubbles in Two-Phase Flows and the Design of a Bubble Sensor for CBM Wells

Wen

Han

et al. 2016

Sensors

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The parameters of gas-liquid two-phase flow bubbles in field coalbed methane (CBM) wells are of great significance for analyzing coalbed methane output, judging faults in CBM wells, and developing gas drainage and extraction processes, which stimulates an urgent need for detecting bubble parameters for CBM wells in the field. However, existing bubble detectors cannot meet the requirements of the working environments of CBM wells. Therefore, this paper reports findings on the principles of measuring the flow pattern, velocity, and volume of two-phase flow bubbles based on conductivity, from which a new bubble sensor was designed. The structural parameters and other parameters of the sensor were then computed, the “water film phenomenon” produced by the sensor was analyzed, and the appropriate materials for making the sensor were tested and selected. After the sensor was successfully devised, laboratory tests and field tests were performed, and the test results indicated that the sensor was highly reliable and could detect the flow patterns of two-phase flows, as well as the quantities, velocities, and volumes of bubbles. With a velocity measurement error of ±5% and a volume measurement error of ±7%, the sensor can meet the requirements of field use. Finally, the characteristics and deficiencies of the bubble sensor are summarized based on an analysis of the measurement errors and a comparison of existing bubble-measuring devices and the designed sensor.

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Model of bubble velocity vector measurement in upward and downward bubbly two-phase flows using a four-sensor optical probe

Cited by 17 publications

References 35 publications

A study on hydrodynamic characteristics in a Φ38 pulsed extraction column by four‐sensor optical fiber probe

A study on hydrodynamic characteristics in a Φ38 pulsed extraction column by four‐sensor optical fiber probe

Comparison of data processing algorithm performance for optical and conductivity void probes

Research on the Conductivity-Based Detection Principles of Bubbles in Two-Phase Flows and the Design of a Bubble Sensor for CBM Wells

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