Process intensification by integration of catalytic and adsorptive functionalities has tremendous potential in energy and biochemical systems. In-situ or integrated catalytic adsorption can lead to higher yield, purity and selectivity compared to conventional reaction processes. The aim of this work is to develop a) multi-scale methodologies to determine the optimal process variables for maximum performance, b) new tools for the design and decision making of high performance sorption enhanced reaction processes. In this work, a unified framework has been developed that integrates continuum model at bulk scale with particle level diffusion-reaction-sorption model for a fixed bed reactor with multifunctional particles. At bulk scale the system is sensitive to various operating parameters like wall temperature, bed voidage and feed compositions etc. Two important particle level characteristics are identified: distribution of catalyst and sorbent inside particles and geometry of particle pores such as the ratio of pore radius to tortuosity. It has been demonstrated that considering an effective diffusivity at particle pore level has a better control on intensification of sorption enhanced reaction processes. Theadsorption capacity of a sorption enhanced reaction bed is limited. The yield and purity from the fixed bed decreases once the adsorption capacity of the bed is exhausted. The regeneration of the used bed along with recycle of the products can lead to continuous production of high purity products. Simulated moving bed reactor is one such process for the production of high quality products by continuous regeneration of a series of fixed bed reactor-adsorbers. In this work, we have developed rigorous dynamic simulation frameworks to achieve efficient operation of industrially relevant energy generation processes, such as steam methane reforming (SMR) for hydrogen production and esterification reactions for biodiesel production. The effect of various operating conditions such as switching time, feed flow rate, eluent flow rate, and length of the unit on the purity and conversion was systematically investigated. Thus optimal operating conditions for high conversion and purity from these processes are achieved. Multi-scale simulation is an emerging discipline that spans over different scales varying from . surface level to continuum level. Multi-scale model can predict the properties of catalyst and adsorbent for optimum operation of the sorption enhanced reaction processes discussed above. In addition to the dynamic simulation methodology, two novel multi-scale methodologies have been proposed a) coarse graining method by wavelet transform of surface level Monte Carlo simulations b) hybrid methodology combining continuum equations at bulk scale and Monte Carlo simulations at surface scale. The coarse grained MC simulations are applied to example problems of CO oxidation on the surface of catalyst and to a generic sequential linear reactions with three components, while hybrid Monte Carlo mean field methodology is applied to the cell cycle data to study the activation of cancer by mitogen activated protein kinase pathway. Furthermore the latter methodology was applied to study the mechanisms of biodiesel transesterification reactions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:507227 |
| Date | January 2009 |
| Creators | Kapil, Ankur |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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