Karki, B, Faraj, Y and Wang, M (2016) Electrical Conductivity Based Flow Regime Recognition of Two-phase Flows in Horizontal pipeline. In: WCIPT8 Proceedings. 8th World Congress on Industrial Process Tomography, 26-29 Sep 2016, Iguassu Falls, Brazil. International Society for Industrial Process Tomography ISBN 9780853163497
Abstract
An experimental method of resolving flow regimes by utilizing the conductivity data measured by Electrical Resistance Tomography (ERT) is presented. The method applies Boolean logic and frequency analysis of the ERT signal in order to identify five typical flow regimes in horizontal pipe namely: bubble, plug, slug, stratified and annular. The relative conductivity signal obtained from the tomograms is converted to binary form in order to perform Boolean logical operation with the binary templates of typical flow patterns. The overall conductivity of the tomogram is used to extract frequency information of the flow. Flow pattern is identified by the statistical analysis of the combination of this information. The recognition method was evaluated using experimental data from horizontal pipeline for different flow conditions. The identification of the flow regimes from the method was verified using the conductivity images from ERT.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016, International Society for Industrial Process Tomography. This is an author produced version of a paper published in WCIPT8 Proceedings. |
Keywords: | electrical resistance tomography, flow regime recognition, multiphase flow |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Funding Information: | Funder Grant number EURAMET EMRP-MSU ENG58-REG2 EURAMET EMRP-MSU ENG58-REG3 |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Nov 2016 13:14 |
Last Modified: | 08 Jun 2018 15:37 |
Published Version: | https://www.isipt.org/world-congress/8/29003.html |
Status: | Published |
Publisher: | International Society for Industrial Process Tomography |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:108720 |