Abstract
Conductivity measurements at different temperatures were undertaken to investigate the variation of conductivity as a function of sodium chloride solid particle concentrations in sodium chloride-saturated aqueous monoethylene glycol (MEG) solutions. A methodology has been developed that is capable of quantifying the relationship between the conductivity measurement, sodium chloride particle concentration, temperature, and MEG concentration in the brine-saturated aqueous solution. The results indicate that the conductivity decreases exponentially as the solid sodium chloride particle concentration increases from 0 to 30 wt%, whereas in the absence solid particles, the conductivity of sodium chloride-saturated aqueous MEG solutions is a polynomial function of temperature and MEG concentration. It is demonstrated that a single, universal empirical model can be developed to quantify the relationship between the conductivity and relevant process parameters across the whole experimental range. The methodology can be readily adopted for in situ monitoring of solid salt particle concentration and estimation of MEG loss in a typical industrial MEG reclamation process, leading to the establishment of more effective process control and operation strategies.
Original language | English |
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Journal | Chemical Engineering Research and Design |
Early online date | 2 Mar 2019 |
DOIs | |
Publication status | Published - 2019 |
Keywords
- Monoethylene glycol (MEG)
- Desalination
- Pilot plant
- Conductivity
- Sodium chloride
- Sedimentation
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Dive into the research topics of 'Operational Study of a Monoethylene Glycol (MEG) Desalination Pilot Plant. Part I: Development of a New Method for the Estimation of MEG Content in the Presence of NaCl Solid Particles'. Together they form a unique fingerprint.Datasets
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Operational Study of a Monoethylene Glycol (MEG) Desalination Pilot Plant. Part I: Development of a New Method for the Estimation of MEG Content in the Presence of NaCl Solid Particles: data
Martin, P. (Creator), Mendeley Data, 20 Aug 2019
DOI: 10.17632/bjhc5t86vw.1, https://data.mendeley.com/datasets/bjhc5t86vw
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