Thermo-physical properties of CO2 mixtures and their impacts on cryogenic carbon capture processes
Abstract: Carbon capture and storage (CCS) is one of the most promising technologies that may significantly reduce CO2 emissions. A better understanding of the thermo-physical properties of CO2 mixtures is required for the design and operation of different CCS processes. Before the knowledge gaps of the property models are being filled, it is important to identify the properties that can significantly influence the processes and find the proper property models. In this thesis, the status and progress of property impacts on CCS processes were reviewed by a literature survey. The studied CCS processes in this thesis include CO2 conditioning, transport, and storage. The results show that heat capacity and density are most important for the pumping process in CO2 conditioning systems, while heat capacity and compressibility have greater impacts on compression processes. In addition, density is the most important in CO2 pipeline transport and CO2 storage.To follow up the knowledge gaps of the property impacts identified in the literature survey, quantitative impacts of the related properties on design and operation of key components including the multi-stream plate-fin heat exchanger and the centrifugal compressor, as well as the cryogenic process performance, were investigated by a sensitivity analysis. The results show that thermal conductivity has the most significant impact on heat exchanger sizing. Density and enthalpy have the most significant impact on the compressor impeller diameter and on the isentropic efficiency. In addition, thermal conductivity has the most significant impact on the capture rate of CO2, CO2 purity, and the operation cost of the cryogenic separation process. Hence, developing a more accurate thermal conductivity model should be prioritized for process design and operation of the cryogenic separation.The performances of the thermal conductivity and viscosity models were evaluated for CO2 mixtures with non-condensable impurities. The results show that the KRW (Kestin-Ro-Wakeham) model is recommended for predicting the viscosity. For estimating thermal conductivity, the GERG (Groupe Européen de Recherches Gazières) model is the most accurate.
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