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Title: Predictive modelling of ash particle deposition in a PF combustion furnace
Author: Degereji, Mohammed Usman
ISNI:       0000 0004 2714 6149
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2011
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Slagging and fouling during the combustion of pulverised coal in boilers is a major problem as power generators strive to improve the efficiency of plants. The coal type has a major influence on the slagging propensity in furnaces. The correlation between predicted results using some of the existing slagging indices and the actual observations made in most conventional boilers has been poor, especially when their use is extended to different coals. In this thesis, a numerical model to predict coal ash particle deposition rate in pulverized coal boilers has been developed. The overall sticking probability of the particle is determined by its viscosity and its tendency to rebound after impaction. The deposition model has been implemented in the Fluent 12.1 software, and the effects of swirling motion ash particle viscosity on deposition rates have been investigated. The predicted results are in good agreement with the reported experimental measurements on the Australian bituminous coals. Also, a novel numerical slagging index (NSI) which is based on ash fusibility, ash viscosity and the content of ash in the coals has been developed. The incoming ash shows significant influence on slag accumulation in boilers. The results of assessment of the slagging potential using the NSI on a wide range of coals and some coal blends correlate very well with the reported field performance of the coals. The NSI has been modified to predict the slagging potential of some coal and biomass blends with < 20% biomass ratio. The results of predictions using the modified index on coals blended with sewage sludge and saw-dust are in good agreement with the experimental data.
Supervisor: Pourkashanian, Mohamed ; Ingham, Derek B. ; Williams, Alan ; Ma, Lin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available