Investigation of the effect of the electrode distance on the impedance void meter performance in the two-phase flow measurement

Zhuoran Dang, Yang Zhao, Guanyi Wang, Peng Ju, Qingzi Zhu, Xiaohong Yang, Robert Bean, Mamoru Ishii

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Experimental study on the effect of electrode distance on the performance of impedance void meter is presented. The study includes multiple approaches. In the numerical simulation approach, based on the mathematical similarity between electric and temperature fields, the electric fields with different electrode distances are simulated using ANSYS Fluent to generate temperature fields. In the experimental study, an adiabatic air-water experiment is performed to compare two impedance meters with different electrode distances. The test conditions cover the flow regimes from bubbly flow to annular flow. Gamma densitometer and multi-single sensor conductivity probe are utilized for the void fraction comparison. The effect of the electrode distance on the flow regime identification using the artificial neural network is investigated, the signals of the different impedance meters are applied as the inputs for the artificial neural network. It is found that impedance meter with a properly large electrode distance has better performance in void fraction measurement, especially at high superficial velocity.

Original languageEnglish
Pages (from-to)283-295
Number of pages13
JournalExperimental Thermal and Fluid Science
Volume101
DOIs
StatePublished - Jan 2019
Externally publishedYes

Funding

This work was performed at Purdue University under the auspices of the U.S. Nuclear Regulatory Commission (NRC), Office of Nuclear Regulatory Research, through the Institute of Thermal-Hydraulics. The authors would like to express their gratitude to technical staff of the NRC for their support on this project.

FundersFunder number
Institute of Thermal-Hydraulics
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Purdue University
National Research Council

    Keywords

    • Drift flux model
    • Experimental comparison
    • Instrumentations
    • Neural network
    • Void fraction

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