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Show PREDICTING COAL QUALTIY EFFECfS ON P. F. FIRING FROM A COAL'S ULTIMATE ANALYSIS INTRODUCTION In the near-burner region of pulverized coal flames, devolatilization supplies the gaseous fuels that ignite and stabilize the flames, and release major portions of the heating value and noxious gases. Total volatiles yields are similar for most coals, but the proportions and compositions of noncondensible gases and tars vary widely. Three phenomenological models have been developed to predict the devolatilization behavior of any coal at any operating conOditions [1-5]. All represent devolatilization as a depolymerization that disintegrates coal's macromolecular structure into smaller volatile fragments with subsequent reintegration of larger intermediates into char. Whereas FLASHCHAIN and the CPD model are based on the same concise set of rate mechanisms, the FG-DVC model is all-encompassing. Each can generate predictions for yields, transient evolution rates, and various product characteristics based on samplespecific characterization data, and CPD and FG-DVC also assign various structural properties of the solid residues. The superior performance of these models can be attributed to their elaborate submodels for coal's macromolecular configuration and chemical constitution. However, along with more illuminating structural features, these approaches incorporate far more input data than classical, two-component models. FLASHCHAIN and CPO have comparable numbers of input parameters, but structural data from 13C NMR analyses is required for every sample with CPO. Whereas FLASHCHAIN entails no laboratory tests whatsoever, FG-DVC has grown into a framework for extensive laboratory work involving state-of-the-art experimental facilities [5]. Since they require such specialized input, neither CPO nor FG-OVC can be used to make predictions for the substantial backlog of experimental studies in the literature, because the infonnation needed to define their input parameters was never acquired. This paper demonstrates FLASHCHAIN's performance for the usual situation where the ultimate analysis is the only sample-specific information available. Results are presented to illustrate the accuracy of the predictions, including the yields from diverse coal types under rapid heating conditions and fuel-nitrogen species distributions. We also 1 |
