Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.577380
Title: Prediction of ash deposition for biomass combustion and coal/biomass co-combustion
Author: Garba, Mohammed Umar
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2012
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Abstract:
In this thesis, a model that couples a reduced alkali kinetic mechanism for alkali sulphate formation during biomass combustion with an ash deposition model using computational fluid dynamics (CFD) techniques has been presented. Starting with a detailed gas-phase kinetic mechanism for the alkali chemistry, a systematic reduction procedure has been performed using a sensitivity analysis to reduce the reaction mechanism to a level that can be implemented into a CFD calculation. An ash deposition model that takes into consideration the ash-sticking probability and the condensation of potassium salts has been developed. The reduced mechanism and the deposition model developed are implemented into a CFD model to predict ash depositions in a 10 MWth biomass grate furnace. Also, a CFD model to predict the deposition rates for the co-combustion of coal with biomass has been developed. This deposition model is based on the combined sticking probabilities of the ash particle viscosity and the melting behaviour of the ash particles. A Numerical Slagging Index (NSI) is also employed to estimate the degree of the sintering of the deposits. Experimental data from the Entrained Flow Reactor (EFR) at Imperial College, London, have been used to validate the models. The predicted results from both the ash deposition models agreed with the experimental measurements, and the NSI has successfully ranked the investigated coal-biomass mixtures according to their degree of sintering.
Supervisor: Pourkashanian, M. ; Williams, A. ; Ma, L. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.577380  DOI: Not available
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