Characterisation and reaction kinetics of high ash chars derived from inertinite-rich coal discards

Thesis (Ph.D. (Chemical Engineering))--North-West University, Potchefstroom Campus, 2007.An investigation was undertaken to determine the gasification and combustion characteristics of chars derived from an inertinite-rich coal discard sample with a high ash content. Fundamental knowledge of the reaction rate kinetics for char conversion at reactions conditions used in fluidised bed gasification and combustion was obtained. For this purpose, characterisation of the parent coal and derived chars, reactivity determinations of the chars and detailed reaction rate modelling was undertaken. The characterisation performed consisted of standard coal analytical methods. petrographic techniques, CCSEM image analysis and a surface adsorption method. The parent coal consists of 32% by volume of inertinite, 7% of vitrinite, 13% of biand tri-macerite, 30% of maceral/mineral mixtures (carbominerite) with 18% of mineral-rich material. Reflectances obtained from measurements taken on vitrinites and total maceral reflectance scans increased dramatically on charring at 900°C and is accompanied by an extension of vitrinite-class distribution. Volatiles were liberated essentially from the original parent vitrinites, creating fine pores. Inertinites increased in reflectance but not in porosity and are characterised as dense char fractions in the final charred product, which was established according to a coal form analysis. Structural change due to low temperature thermal stress fracturing ("passive deflagration") occurred early on in the temperature regimes, creating increased surface areas and porosity. The chars consist of a high proportion (52%) of extraneous rock fragments together with minerals mainly as fine inclusions in carbon rich particles. The chars have very low porosities and surface areas created by devolatisation of maceral associations and deflagration. Combustion and gasification reactivity experiments were carried out in a thermogravimetric analyser at 87.5 and 287.5 kPa pressures between 700 and 900'C and with varying mixtures of oxygen/nitrogen and carbon dioxide/nitrogen mixtures respectively. The effects of temperature, pressure, gas composition and particle size on reactivity were found to confirm well-established trends. The effect of temperature in the high temperature range was, however, strongly affected by pore and film diffusion during combustion. Models based on the random pore model without and with pore diffusion incorporating the properties of the char (porosity. ash content, and derived structural parameter) and structural mechanisms concerning carbon removal, were successfully solved and validated against experimental results. As a result of the complexity of the models consisting of many unknown parameters, a procedure consisting of step-wise regression was developed and applied successfully. This procedure uses a unified carbon conversion versus a reduced time parameter plot with the latter defined as real time/time for 90% conversion. It was found that for char panicles with a mean diameter of 1mm prepared at 900°C. the random pore model (chemical reaction controlling) was applicable for predicting the gasification reaction rate with carbon dioxide-nitrogen mixtures at temperatures up to 9OO'C, whereas for the combustion reactions with oxygen-nitrogen mixtures an adapted chemical reaction-pore diffusion model was found to be applicable in the temperature range 450 to 600°C. The model is characterised by a variable Thiele modulus which can account for pore- diffusion and can undergo a transition to a chemically controlled reaction as a result of the depletion of carbon in the carbon/mineral matrix. Intrinsic reaction rate parameters for gasification and combustion are reported and compared with published results, and were Sound to be slightly different. Diffusion coefficients were also evaluated from the combustion reaction results and found to compare very well with predictions with the Knudsen diffusion model.Doctora