An optimised advanced ash fusion test for power generators

Abstract

The Ash Fusion Test (AFT) is considered to be the most popular method of characterising the melt characteristics of solid fuel ash. This thesis shows how pellet preparation can make significant improvements to repeatability and how the optimised advanced ash fusion test (OAAFT) curve can be used to indicate melting properties. A fully automated analysis technique and novel pelleting method have been developed for the advanced ash fusion test (AAFT) and for the first time it has been directly shown that cones and the hand pressed pellets do not have good repeatability and delay the response of the initial deformation temperature (IDT). The optimum shape parameter to track during the AAFT was identified and software was developed to plot this new OAAFT. The second half of this thesis documents an array of investigations to validate and understand the significance of the OAAFT curve. Varying the levels of SiO2, Al2O3, CaO, Fe2O3, and MgO within pseudo pellets revealed the impact each component on the curve and aligned well with results from literature. Comparisons of the OAAFT curves with FactSage prediction identified the coals to have excellent correlation whereas the biomass requires further work. Preliminary work on grouping the OAAFT suggested that it can be used to identify links to individual species in samples. The key trends greater levels of SiO2 and lower levels of CaO and SO3 result in an expansion phase. An industrial investigation highlighted the potential for the OAAFT to be used in alternative applications. Fuel feed stocks for 2 Colombian stoker furnaces were imaged during combustion to identify swelling, up to 130%, in some of the coals