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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Chapoy, Antonin
Heriot-Watt University
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (6/6 displayed)
- 2020Elemental Mercury Partitioning in High Pressure Fluids Part 2: Model Validations and Measurements in Multicomponent Systemscitations
- 2017Glycols Partitioning At High Pressures In Gas Processing Systems
- 2013Effect of impurities on thermophysical properties and phase behaviour of a CO2-rich system in CCScitations
- 2012An evaluation of risk of hydrate formation at the top of a pipelinecitations
- 2011Equilibrium water content in natural gas with hydrates or MEG solutions
- 2010Hydrates in High Inhibitor Concentration Systems
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article
Elemental Mercury Partitioning in High Pressure Fluids Part 2: Model Validations and Measurements in Multicomponent Systems
Abstract
A good understanding of the solubility of elemental mercury over wide ranges of temperature, pressure and composition is an important issue to assess the possibility of mercury dropping out in gas processing streams. In this work, new mercury solubility in three multicomponent systems with methane content varying between 89 – 26 mol% have been measured over a wide range of temperature (243.15 to 323.15 K) and pressure and up to 20 MPa.A group contribution method for the Peng-Robinson equation of state has been used to allow calculation of binary interactions between mercury and saturated hydrocarbons, aromatic hydrocarbons, nitrogen and carbon dioxide. The parameters of the group contribution have been adjusted using mercury solubility previously measured in single components. Predictions of the developed model are validated against independent experimental data and the data generated in this work. A good agreement between predictions and experimental data is observed, supporting the reliability of the developed model.