Predictive modelling of ash particle deposition in a PF combustion furnace

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

Ash deposition propensity of coals/blends combustion in boilers: a modelling analysis based on multi-slagging routes

A method that is based on the initial slagging routes and the sintered/slagging route has been developed and used for predicting the ash deposition propensities of coal combustion in utility boilers supported by the data collected from power stations. Two types of initial slagging routes are considered, namely (i) pyrite-induced initial slagging on the furnace wall, and (ii) fouling caused by the alkaline/alkali components condensation in the convection section. In addition, the sintered/slagging route is considered by the liquids temperature, which represents the melting potential of the main ash composition and is calculated using the chemical equilibrium methods. The partial least square regression (PLSR) technique, coupled with a cross validation method, is employed to obtain the correlation for the ash deposition indice. The method has been successfully applied to coals/blends combustion in boilers, ranging from low rank coals to bituminous coal. The results obtained show that the developed indice yields a higher success rate in classifying the overall slagging/fouling potential in boilers than some of the typical slagging indices. In addition, only using the SiO2/Al2O3 ratio to predict the melting behaviors and slagging potential is inaccurate since the effect of the SiO2/Al2O3 ratio is dictated by both the original ash composition and the way in which the SiO2/Al2O3 ratio is changed. Finally, the influence of the acid components (SiO2 and Al2O3) on the ash deposition prediction is investigated for guiding the mineral additives. It is noticed that the predicted ash deposition potentials of the three easy slagging coals investigated decrease more rapidly by adding Al2O3 than by adding SiO2

Measurements and CFD modeling of a pulverized coal flame with emphasis on ash deposition

Measurements of fly ash deposition in a 15 kW pulverized coal jet flame and CFD-based mathematical modeling have been performed. The deposits have been collected at two ports at particle Stokes numbers in the 0.02–0.34 range and particle kinetic energies not larger than 2×10-92×10-9 J. Inertial impaction and thermophoresis have been identified as main mechanisms of particle transport towards the deposition surfaces. Deposition rates on air-cooled probes (View the MathML source600–700°C surface temperature) have been measured to be 24% (Port 2) and 79.4% (Port 3) larger than those measured on uncooled probes (View the MathML source1150°C surface temperature) due to the enhanced role of thermophoresis. Complex dependencies of the deposition rate on the probe surface temperature and the probe location have been observed. The CFD-model predictions are able to reproduce these dependencies after adjustments to the particle sticking sub-model. The paper contains estimations of both the impaction and sticking efficiencies