Enhancing packed bed geometry using computational fluid dynamic simulations
Degree GrantorUniversity of Canterbury
Degree NameMaster of Engineering
This work comprises an investigation into how the efficiency of packed beds can be enhanced by manipulating the geometry of the channel network, without altering the process chemistry. A particular focus is placed on investigating how the morphology of the structures influences the mass transfer properties of a passively transported solute species. This includes the degree of axial dispersion and the breakthrough performance of an adsorption column. Using computational fluid dynamic modelling techniques (the Lattice Boltzmann Method) periodic representations of ordered sphere packing and Triply Periodic Minimal Surface (TPMS) structures were subject to laminar flow conditions to compare the mass transport properties. The model parameters were derived from a proposed novel sorption filter for removal of trace heavy metal contaminants from water sources, although the results are expected to be relevant to many other applications.
A detailed outline of the modelling techniques is given, before addressing the performance of each geometry tested. Initially, traditional packing media (arrangements of spherical particles) were compared with TPMS monolithic structures. After confirming that TPMS structures provide enhanced packed column properties when compared with particle arrangements, additional TPMS and manipulated TPMS structures were considered. Parameters describing the geometry and flow fields within each structure are shown to correlate with chromatographic performance and column breakthrough. The relationships between solid phase distribution and enhanced packed bed performance provide a good basis for further investigations into refining packed bed geometry. The Schwarz Diamond and Double Schoen Gyroid TPMS structures were identified as the best performing of the structures that were modelled. Additionally, several practical suggestions are made to assist with the implementation of these findings, such as the expected dimensions of a real system and the sensitivity of results to operating parameters.