(222ah) Comprehensive Thermophysical Model Development for CO2 Pipeline Transport

Carbon Capture and Sequestration (CCS) is one of the most promising technologies for the reduction of CO₂ accumulation in the atmosphere. Flue gas sources such as power plants and other manufacturing processes that depend heavily on fossil fuels, can be equipped with systems that capture the CO₂ from the flue gas stream, and then transport the CO₂-rich stream via pipelines to places where oil reservoirs near depletion, saline aquifers, or other underground cavities, can receive and store the CO₂.

The part of CO₂ pipeline transport is often overlooked and simulated using models developed for natural gas transport. However, its importance raises the need for multi-disciplinary research on the details involved, that are substantially different than natural gas. In particular, since the CO₂ pipeline networks may run close to populated areas, thorough hazard assessment studies are required both for the regulatory frameworks and the social acceptance campaigns. A hazard assessment study is based on fluid calculations in and out of the pipeline, such as normal flow, and dispersion in the event of a rupture. All these calculations rely heavily on the models used for the prediction of thermophysical properties of the fluids involved, which are mainly CO₂ mixtures with other gases.

A large number of properties are necessary for the aforementioned calculations, ranging from density and compressibility, to derivative thermodynamic properties such as speed of sound and the Joule-Thomson inversion curve, and even further to transport properties that include viscosity and self-diffusion coefficient. By employing an accurate, robust, and reliable thermodynamic model that covers the entire range of properties and conditions, improved quality of hazard assessment studies can be ensured.

In this work, several equations of state (EoS) have been assessed for their capabilities of predicting accurately the thermodynamic properties of CO₂ mixtures with other gases. Extensive comparisons with literature experimental data have been performed, showing the similarities of the approaches in relatively simple properties such as density and vapor-liquid equilibria, while pointing out the superiority of higher order EoS (i.e. PC-SAFT) when it comes to more complex properties such as derivative thermodynamic and transport properties. More specifically, the derivative thermodynamic properties are calculated by analytically derived expressions, which means that the computational cost is kept low, while the physical background of each approach is tested. On the other hand, transport properties include the notion of time, thus it is conceptually impossible to be calculated by equilibrium thermodynamic models that do not take into account time. To overcome this obstacle, several established models of the literature have been combined with the EoS, and re-tuned, in order to extend the properties calculation framework to those properties.

Phase equilibria and saturated density calculations for pure components were the starting point, while moving toward mixtures, experimental data were used to optimize the binary interaction parameters. Analytical expressions for the thermodynamic derivative properties were derived for every EoS, and checked against the numerical derivatives, ending with the comparison of all EoS against experimental data available in the literature. Viscosity models both for pure components and mixtures were linked to the EoS, and the use of the meta-heuristic optimization method of Particle Swarm Optimization aided the production of the parameters’ tables. Calculations for mixtures of CO₂ were compared with a few experimental data available in the literature and the agreement was excellent in all cases. Furthermore, gaps of experimental data were identified, in order to act as a suggestion for future experimental work. The combined approaches and the new optimized parameters constitute integral parts of a broader thermodynamic simulator that was developed in this project.

Several useful conclusions are drawn from this work, that can be used further to simulators dedicated to the pipeline transport part of the CCS process. Higher order EoS, such as PC-SAFT and the like, can predict more accurately the thermodynamic properties of the systems of interest, while the overhead computational cost is marginally higher than the cost for a cubic EoS. Especially the derivative thermodynamic properties point out the power of higher order EoS over cubic EoS since the latter usually exhibit high discrepancies compared to experimental data. Transport properties can be very efficiently calculated via the combination of an EoS with an appropriate model, given that the parameters have to be re-tuned in order to achieve a good fit for the respective reference systems and states. In this work, several optimization exercises have been performed in order to come up with the parameter values for each EoS and every model.