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Title: Post-combustion CO2 capture by adsorption processes
Authors: Haghpanah, Reza
Keywords: DRNTU::Engineering::Chemical engineering::Processes and operations
Issue Date: 2013
Abstract: In the past decade, a general consensus that global warming is real and there is a close correspondence between the increase in atmospheric CO2 concentration and the global climate change has been reached. Several approaches are being considered to reduce CO2 emissions and to mitigate climate change, e.g., switch to renewable energy sources, use of less carbon intensive fuels, improve process efficiency, carbon capture and sequestration (CCS), etc. Carbon dioxide capture and sequestration, which seeks to concentrate the CO2 from emission sources and sequester them in geological formations, is now considered a technologically viable solution for mitigating climate change. Absorption, currently the most preferred process for CO2 capture, is energy intensive preventing its large-scale deployment. This has created a need to develop alternative technologies for concentrating CO2. Adsorption has been reported to be candidate for CO2 capture from point sources such as power and chemical plants. Conventional adsorption processes have been designed and optimized for the purification of the light gas. However, in carbon capture, the challenge is to recover the heavier product, i.e., CO2 in high purity. This requires novel cycles that incorporate different steps for extract enrichment. Although these process alternatives have been reported in the literature, an objective comparative study of various processes on a common platform is still lacking/missing. In order to achieve the goal of process design several fundamental studies, including measurement of equilibrium, column dynamics are essential. In present study, a new method for extracting model-independent discrete equilibrium data from a set of dynamic column breakthrough experiments is described. Instead of the classical approach, where an isotherm model, i.e., a function, is used to describe the equilibrium, this approach represents the isotherm as a set of discrete points. For a given set of discrete fluid phase concentrations, an optimization method is used to determine the corresponding solid loadings that lead to the best-fit prediction of the experimental breakthrough profile. In this work, we develop the algorithm and validate it using single-component case studies, for a variety of isotherm shapes. The practical use of the method is demonstrated by applying it to experimentally measured breakthrough profiles. In this work, we systematically analyze most known pressure vacuum swing adsorption (PVSA)/vacuum swing adsorption (VSA) cycles with zeolite 13X and carbon molecular sieve as the adsorbent to capture CO2 from dry, post-combustion flue gas containing 15% CO2 in N2. We also report full optimization of the analyzed VSA cycles using Genetic Algorithm (GA) to obtain purity-recovery and energy-productivity Paretos. The roles of individual steps and operating conditions on the performance of the PVSA/VSA process are investigated. The synthesized PVSA/VSA configurations are assessed for their ability to simultaneously produce high purity CO2 at high recovery. Finally, the configurations that meet the 90% purity-recovery constraints are ranked according to their energy-productivity Paretos. Looking beyond CO2 capture, this thesis developes a solid framework for the design and optimization of cyclic adsorption processes. It can be readily used for other separation problems and design of novel adsorbent materials.
Fulltext Permission: restricted
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Appears in Collections:SCBE Theses

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