Sun, Shijie, Zhang, Wenbiao, Sun, Jiangtao, Cao, Zhang, Xi, Lijun, Yan, Yong (2018) Real-time Imaging and Holdup Measurement of Carbon Dioxide under CCS Conditions Using Electrical Capacitance Tomography. IEEE Sensors Journal, 18 (18). pp. 7551-7559. ISSN 1530-437X. E-ISSN 1558-1748. (doi:10.1109/JSEN.2018.2858448) (KAR id:68831)
PDF
Author's Accepted Manuscript
Language: English |
|
Download this file (PDF/1MB) |
Preview |
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: https://doi.org/10.1109/JSEN.2018.2858448 |
Abstract
This paper presented a method for real-time cross-sectional imaging and holdup measurement of gas-liquid two-phase carbon dioxide (CO2) flow using electrical capacitance tomography (ECT). A high-pressure ECT sensor with 12 electrodes was constructed and a dedicated digital ECT system with a data acquisition rate of 757 frames/s was developed for capacitance measurement. Three widely used image reconstruction algorithms were compared for tomographic imaging and phase holdup measurement. Experiments were carried out on a DN25 laboratorial scale CO2 two-phase flow rig at a pressure of 6 MPa for the gaseous mass flowrates from 0 to 430 kg/h and liquid mass flowrates at 515, 1100, and 1900 kg/h. The experimental results show that the cross-sectional distribution of two-phase CO2 flow can be monitored using the ECT system, which matches well with the images captured by a high-speed imaging system. Compared with the reference gas holdup obtained by the flowmeters in the single phase gaseous and liquid loops, the absolute accuracy of the gas holdup measurement can reach 6%, indicating that the developed system is promising for real-time monitoring of carbon dioxide in carbon capture and storage transportation pipelines.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1109/JSEN.2018.2858448 |
Uncontrolled keywords: | Electrical capacitance tomography, Carbon dioxide;-, transport, Image reconstruction, Holdup measurement |
Subjects: | T Technology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Yong Yan |
Date Deposited: | 28 Aug 2018 10:29 UTC |
Last Modified: | 05 Nov 2024 12:30 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/68831 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):