Modeling and uncertainty quantification of CO2 absorption process using phase separation solvent
•CO2 absorption process using phase separation solvent is modeled.•Vapor liquid equilibrium was modeled as a pseudo single phase solvent.•Three different vapor–liquid equilibrium models are considered and compared.•Model parameters are estimated from solubility tests and lab-scale absorber tests.•Pa...
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Veröffentlicht in: | Chemical engineering science 2024-10, Vol.298, p.120348, Article 120348 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •CO2 absorption process using phase separation solvent is modeled.•Vapor liquid equilibrium was modeled as a pseudo single phase solvent.•Three different vapor–liquid equilibrium models are considered and compared.•Model parameters are estimated from solubility tests and lab-scale absorber tests.•Parameter uncertainty is quantified by Markov chain Monte Carlo method.
Absorption using an amine solvent is one of the primary means for capturing CO2 from many combustion sources such as fossil fuel power plants. CO2 capture systems by absorption need a large amount of thermal energy to strip CO2 from the amine solvent. In recent years, absorption using a phase separation solvent, which forms two phases when CO2 is absorbed, has been demonstrated as a promising technique to reduce the energy consumption. In this study, we examine several process models for the CO2 absorption process using a phase separation solvent, and quantify the uncertainty of the model parameters. We estimated model parameters, including equilibrium and mass transfer parameters, from two sources of experimental data: solubility tests, as well as lab-scale absorber tests. Model parameters were estimated by Bayesian inference using the Markov chain Monte Carlo method. The proposed approach successfully quantified the uncertainties of the model parameters. |
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ISSN: | 0009-2509 |
DOI: | 10.1016/j.ces.2024.120348 |