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Title: Computational modelling of the condensation process of the fast pyrolysis vapours in liquid collection systems
Author: Palla Venkata Satya, K. K.
ISNI:       0000 0004 6058 3324
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2015
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The aim of the present thesis is to model the conversion process of the fast pyrolysis vapours into liquid bio-oil in liquid collection systems. The study focuses on the two major types of condensation systems namely the indirect contact condensers and the direct contact condensers (quenching columns). In the first part of the research, the hydrodynamic and heat transfer characteristics of a bench scale quenching column are presented by conducting numerical simulations based on the immiscible Eulerian-Eulerian model. The simulations are compared with experimental observations on flooding phenomena and various design variants are proposed for their elimination. In the second part, a multiphase multi-component model, with the condensable vapours and non-condensable gases as the gaseous phase and the condensed bio-oil as the liquid phase, has been developed. Species transport modelling has been used to capture the detailed physical phenomena of 11 major compounds present in the pyrolysis vapours. The development of the condensation model relies on the saturation pressures of the individual compounds computed based on the corresponding state correlations. In the final part, detailed information is provided on the vapour phase change dynamics implemented on a disc and donut quenching column design obtained from the first part. The study investigates the effect of the different numbers of disc and donut pairs on the condensation performance of the column. The numerical simulations showed that different number of stages can significantly affect the final bio-oil composition. It is shown that heavy molecular weight compounds, condense rapidly even with a low number of stages, whereas an increased number of stages is needed to completely capture the heavier acidic fractions. The modelling results are in good agreement with data published in the existing literature.
Supervisor: Papadikis, K. ; Xiaoxiang, Z. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral