303366 Statistical Modelling of Constituents in Ash Evolved From Pulverized Coal Combustion

Esam I. Jassim, Mechanical Engineering, Prince Mohammad Bin Fahd University, Al-khobar, Saudi Arabia and Hassan Abdulmouti, Mechanical, PMU, Al-Khobar, Saudi Arabia

Industries using conventional fossil fuels have an interest in better understanding the mechanism of particulate formation during combustion since such is responsible for emission of undesired inorganic elements that directly impact the atmospheric pollution level. Fine and ultrafine particulates have tendency to escape the flue gas cleaning devices to the atmosphere. They also preferentially collect on surfaces in power systems resulting in ascending in corrosion inclination, descending in the heat transfer thermal unit, and severe impact on human health.  This adverseness manifests particularly in the regions of world where coal is the dominated source of energy for consumption.

 This study highlights the behaviour of calcium transformation as mineral grains verses organically associated inorganic components during pulverized coal combustion. Theinfluance of existing type of calcium on the coarse, fine and ultrafine mode formation mechanisms is also presented. The impact of two subbituminous coals on particle size and calcium composition evolution during combustion is to be assessed. Three mixed blends named Blends 1, 2, and 3 are selected according to the ratio of coal A to coal B by weight. Calcium percentage in original coal increases as going from Blend 1 to 3.

 A mathematical model and a new approach of describing constituent distribution are proposed. Analysis of experiments of calcium distribution in ash is also modelled using Poisson distribution. A novel parameter, called elemental index λ, is introduced as a measuring factor of element distribution.

 Results show that calcium in ash that originally in coal as mineral grains has index of 17, whereas organically associated calcium transformed to fly ash shown to be best described when elemental index λ is 7.


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