Polypropylene production in a fluidised BED catalytic reactor: Comprehensive modeling, optimisation and pilot scale experimental validation / Mohammad Jakir Hossain Khan

Mohammad Jakir, Hossain Khan (2017) Polypropylene production in a fluidised BED catalytic reactor: Comprehensive modeling, optimisation and pilot scale experimental validation / Mohammad Jakir Hossain Khan. PhD thesis, University of Malaya.

	PDF (The Candidate's Agreement) Restricted to Repository staff only Download (1610Kb)
Preview	PDF (Thesis PhD) Download (7Mb) | Preview

Abstract

There is wide range of applications in chemical processes and energy generation in the experimental and numerical studies of multiphase flows. General uses include fluidised bed catalytic polymerization, fluidised bed reactors (type of chemical reactors), process parameters optimization, such as temperature, system pressure, monomer concentration, catalyst feed rate, superficial fluid velocity and vital technology breakthrough in various polyolefin based engineering. Via the use of Computational Fluid Dynamics (CFD) methods combined with mathematical and statistical model, this thesis concentrated on the investigation of bubble and emulsion phase dynamic transitions on polypropylene production rate. The use of ANNOVA (Analysis of variance) method with Response Surface Methodology (RSM) was used to statistically model the experiments to validate and identify the process parameters for polypropylene production was conducted by. Reaction temperature, system pressure and hydrogen percentage were the three important process variables and important input factors in the performed analysis of polypropylene production. Through the evaluation of the effects of the process parameters and their interactions, statistical analysis indicated that the proposed quadratic model had a good fit with the experimental results. The highest polypropylene production of 5.82% per pass was obtained at an optimum condition with temperature of 75 °C, system pressure of 25 bar and hydrogen percentage of 2%. With the combination of statistical model and CFD (computational fluid dynamic) method, a hybrid model was developed to explain the detailed phenomena of the process parameters. A series of experiments were also conducted for propylene polymerisation by changing the feed gas composition, reaction initiation temperature and system pressure in a fluidised bed catalytic reactor. During reaction, 75% monomer concentration (MC) was shown as the optimum propylene concentration. The multiphasic reaction models tested in this research supposed that polymerisation happened at both in the emulsion and the bubble phase. With respect to the experimental range of the superficial gas velocity and the catalyst feed rate, it was observed that the ratio of the polymer created during the bubble phase, as compared to the overall rate of production, was approximately in the range of 9.1-10.8%. This was a noteworthy quality and should not be looked over. Two different solvers were used to achieve fluid flow computation. One of them was ANSYS FLUENT which was a general-purpose CFD code expanded from UDF (user defined functions) method on a collocated grid. The expanded UDF had various physical models that could be used in a wide range of industries. The other solver was Design Expert which was developed for the optimization of a broad range of process parameters. Multiphasic model was a general-purpose hydrodynamic model that validated chemical reactions and dynamic profiles of gas-solid flow in real reaction situations that usually occurred in olefin polymerization and chemical processing reactors. It was observed that the enhanced hybrid and multiphasic models were able to forecast more constricted and safer windows at analogous conditions as compared to the experimental results. Conversely, the enhanced models had similar dynamic behaviour as the conventional model during the initial stages of the polymerisation but deviated as time progressed. Characterizations studies were conducted on the polypropylene and resulted in detailed information on the effects of the different process parameters on the product.

Actions (For repository staff only : Login required)