Work

Model for prediction of strength of ash deposits

Year: 2004
Type: dissertation
Abstract: Ash formed during combustion of pulverized coal in utility boilers causes a variety of problems, including adhesion to heat transfer surfaces, corrosion and erosion.Approximately 20-40 % of ash formed in pulverized coal (PC) -fired utility boilers deposits in the hopper at the bottom of furnace and internal surface as slag.60-80 % of ash is carried by flue gas and can deposit in the convective pass on steam tubes.The primary objective of the project is to develop a model to predict strength of ash deposits (on boiler tubes) as a function of ash chemistry and temperature.The main two terms in the model relate surface tension/viscosity to strength and porosity to strength.For this project values of surface tension, viscosity and a sh d eposition rate/ash feed rate were available from previous work done at Energy and Environmental Research Center at University of North Dakota.Values for porosity and shear strength were found by experimentation for this project.Graphical and statistical study of the available and experimental data was done.Statistical study mainly involved regression analysis for finding significance of factor.Ash deposition rate/ash feed rate was found to be strongly correlated to surface tension/viscosity.For porosity, no correlation with ash deposition rate was found.Deposit strength was measured for all 40 samples at room temperature by hand, feeling how much force was required to crush the sample in between fingers.Each sample was given a crush rating, called a "finger factor", on a scale of 1-5 with 5 being the strongest.The shear strength of ten samples (2 at each finger factor value) were measured at high viii temperature (1050℃) and found to correlate very well with the finger factor, so a shear strength was correlated for all samples from the finger factor value.Shear strength showed no graphically obvious correlation with either factor.Also statistical analysis showed no correlation between shear strength and both the factors.
Language: English
Open Access status: green
OpenAlex ID: W7168437325
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