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dc.contributor.authorKlotz, Adeline Rachelle
dc.date.accessioned2019-07-08T13:41:38Z
dc.date.available2019-07-08T13:41:38Z
dc.date.issued2019-07-19
dc.date.submitted2019-03-20
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/294445
dc.description.abstractThis thesis presents the implementation and development of nuclear magnetic resonance (NMR) techniques to study mass transfer and hydrodynamic phenomena that govern the performance of packed bed reactors. The aim of this work is to gain insight into factors that affect the process of fines deposition and mass transfer inside packed beds to ultimately enable optimisation of these processes. Although mass transfer correlations exist for pure components and mixtures, previous studies have failed to measure the mass transfer coefficient in situ without extensive pre-calibration. In this thesis, the T2-T2 method is used to measure in situ mass transfer coefficients for single components and mixtures without any prior calibration. For mixtures, the standard T2-T2 method was modified to achieve chemical selectivity. Both single component and mixture mass transfer coefficients were found to be in accordance with a semi-theoretical correlation. Moreover, depending on the Reynolds (𝑅𝑒) and Schmidt (𝑆𝑐) numbers characterising the systems, it was illustrated that traditional mass transfer correlations can under-predict mass transfer coefficients in excess of 96% due to incorrect assumptions. For accurate design or modelling of packed beds characterised by low 𝑅𝑒 and 𝑆𝑐, this highlights the need for reconsidering the use of traditional mass transfer correlations. In addition, despite mass transfer correlations existing for mixtures, none address the non-ideal mixture effects upon the mass transfer coefficient. Although the chemically selective T2-T2 method was validated using ideal gas mixtures, some suggestions were offered for non-ideal mixtures that this pulse sequence can study in the future. Despite a plethora of existing studies on fines deposition, none have experimentally validated the pore-scale nature of deposits in realistic packed beds; neither have they considered how the mass transfer rate is affected by deposits. For the first time, through the combination of NMR velocimetry, compressed sensing, a pore analysis, and T2-T2 experiments, pore-scale phenomena were observed in a realistic bed, the guiding principles behind fines deposition were uncovered, and mass transfer coefficients between the bulk and pellet phase were measured. For two types of fines, the pore-scale fines deposition mechanism was identical. Both types of fines also experienced similar decreases in the mass transfer coefficient compared to the clean bed – for just under a five time increase in the pressure drop caused by more fines depositing, the mass transfer coefficient decreased by 40% and 47%, respectively. These results illustrate that standard correlations will over-predict the mass transfer coefficient if fines deposits are not accounted for. Monte Carlo simulations were also used to support the experimental findings, further illustrating that the mass transfer rate is affected by changes to the velocity, voidage, surface area and bed morphology that result from fines depositing. Furthermore, the properties of the fines appeared to only affect the number of molecules participating in mass transfer, and not the mass transfer rate itself. Lastly, comparison between the experiments with the two types of fines illustrated that verifying models by macroscopic experimental variables alone will not be a robust indicator of pore-scale fines deposition phenomena.
dc.description.sponsorshipFunded by Gates Cambridge Trust
dc.language.isoen
dc.rightsAll rights reserved
dc.subjectmass transfer
dc.subjecthydrodynamics
dc.subjectnuclear magnetic resonance
dc.subjectpacked bed reactor
dc.titleTowards an understanding of mass transfer and hydrodynamics in packed bed reactors using Nuclear Magnetic Resonance
dc.typeThesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (PhD)
dc.publisher.institutionUniversity of Cambridge
dc.publisher.departmentChemical Engineering and Biotechnology
dc.date.updated2019-06-13T18:40:26Z
dc.identifier.doi10.17863/CAM.41546
dc.publisher.collegeTrinity college
dc.type.qualificationtitlePhD in Chemical Engineering
cam.supervisorGladden, Lynn Faith
cam.thesis.fundingfalse


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