Computational Thermodynamics of Systems Containing Associating Molecules

Abstract

Thermodynamic modeling is a powerful tool in studying the behavior of physical systems, guiding experimental design and operational conditions, and predicting equilibrium properties. A powerful thermodynamic model saves time and resources in experimental studies and in the design of industrial processes, enabling more efficient and safer operation. In this thesis, the phase equilibria of systems containing bitumen, water, light and intermediate alkanes, toluene, hydrogen, dimethyl ether, and monoethynene glycol are studied by using two- and three-phase flash calculations and stability analysis. The utilized EoSs are based on Wertheim’s thermodynamic perturbation theory (TPT). The cubic plus association (CPA) EoS, based on the first-order thermodynamic perturbation theory (TPT1), is applied to normal alkane/bitumen, water/bitumen, water/normal alkane, and water/bitumen/normal alkane. Initially, the CPA EoS is adjusted by using the liquid-liquid equilibria (LLE) data, which allows the LLE-tuned model to predict vapor–liquid equilibrium (VLE) behavior successfully. Subsequently, the CPA EoS is further parametrized using experimental data of normal alkane/bitumen, water/bitumen, and water/normal alkane systems. The model's predictive capability is then investigated using experimental three-phase data for the water/bitumen/normal alkane system. The model's predictive capability motivated and enabled the development of a ternary phase diagram of water/bitumen/normal alkane. The phase equilibria regions are constructed as a function of feed composition. This computational framework is then validated by experimental data. In addition to the CPA EoS, the perturbed-chain statistical associating fluid theory (PC-SAFT) is employed to evaluate its predictive capability for the phase behavior of the water/synthetic condensate system, using binary-tuned models to predict the multicomponent mixture behavior. The Tz diagram of the system is constructed using both models, and their predictions are validated against experimental data. The models successfully detected the phases in all experiments and predicted the trend in molar composition. Subsequently, higher-order terms of TPT are used. The theory is developed for a spherical particle with four patchy sites and validated by Monte Carlo (MC) simulation. The model is applied to pure monoethylene glycol and its binary mixtures with light gases. The theory outperformed the TPT1-based model in predicting liquid density and vapor pressure.