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Show constant, while C O yields increase; (3) Chain hydrocarbons are converted initially into CH4 and C2H2 then CH4 disappears, and (4) H C N and H2 yields increase throughout secondary pyrolysis. To support CFD applications, the model is being used to •dentify the parameter values in the simple devolatilization rate expressions used in CFD simulations that mimic the FLASHCHAIN predictions, as descnbed previously (Niksa and Cor. 1997). Our virtual coal laboratory concept also enhances traditional combustion engineenng approaches. One application, in which FLASHCHAlN-based yields and nitrogen release for coal flame conditions are used as 'egression variables to predict N O x and LOI emissions from fuii-scale utility boilers, is descnbed in another paper at this conference Additional applications of this approach are developing steadily, including the following: • A fuel supplier's software package to manage all aspects of coal transport, handling, combustion and emissions for coal-burning utilities had previously relied on lab testing to charactenze coal quality impacts. They recently replaced two of the five most expensive tests with a virtual coal laboratory, and are currently replacing a third test. • Results of a laboratory test could reliably forecast which coals would form intolerable deposits within the supply tubes to utility burners. A FLASHCHAIN-based regression of this database has a 9 4 % correlation coefficient and the correlation accurately identified all the most troublesome coals to date. • Similarly, lab tests successfully charactenzed the autoignition propensities of Indonesian coals but were expensive and slow. This database could also be correlated within useful quantitative tolerances with FLASHCHAIN-based regression variables. • A virtual coal laboratory was used to train a neural network furnace control system to regulate the combustion of various coals to meet regulations on NOx and unburned carbon emissions. ACKNOWLEDGEMENTS The expansion of FLASHCHAIN for applications with oetroieum coke and biomass was sponsored in part by the Electnc Power Research Institute and administered by Mr. J. Stallings of EPRI's Energy Conversion Division. REFERENCES Brumsma. 0 S. L , Geertsma, R. S., Bank, P., Moulijn, J. A. (1988), Fuel. Vol. 67. p.334. Cai H. (1995), Ph. D thesis, Dept. of Chemical Engr. and Chemical Technoi., Impenal College, Univ. of London. Chen. J C, Castagnoli, C , Niksa, S. (1992), Energy Fuels, Vol. 6, p 264. Y. Chen, S. Charpenay, A. Jensen, M. A. Wojtowicz, and M A. Seno (1998), Twenty-Seventh Int. Symp on Combust.. Combustion Institute, Pittsburgh pp 1327- 1334. Cho, S., Marlow, D., Niksa. S. (1995), Combust. Flame. Vol 101. p.399. Fraga, A.-R., A. F. Gaines, et al. (1991). Characterization of biomass pyrolysis tars produced in the relative absence of extraparticle secondary reactions. Fuel. Vol. 70(7), pp 803-809. Hajaligol, M. R.. J. B. Howard, et al. (1982) Product compositions and kinetics for rapid pyrolysis of cellulose Ind. Eng. Chem. Process Des. Dev , Vol. 21, pp 457- 465. Jensen, A., K. Dam-Johansen, et al. (1998). TG-FTIR study of the influence of potassium chloride on wheat straw pyrolysis. Energy Fuels, Vol. 12(5), pp. 929-938 Marlow, D., Niksa, S., Kruger, C. H. (1992), Twenty-Fourth Int. Symc on Combust.. Combustion institute. Pittsburgh, p.1251. Nelson, P. F., Tyler, R. (1986). Twenty-First Int. Symp on Combust., Combustion Institute, Pittsburgh, p 427 Nik-Azar. M., M. R. Hajaligol, et al. (1997). Mineral matter effects in rapid pyrolysis of beech wood Fuel Process Technoi., Vol. 51, pp. 7-17 Niksa, S. (1995a), Combust. Flame, Vol. 100. p.384 Niksa, S. (1995b), Energy Fuels. Vol. 9. p. 467 Niksa, S., Coal Combustion Modelling (1996), No.31. IEA Perspectives Series. IEA Coal Research. London Niksa, S. and J J. Cor (1997). Predicting coal quality impacts on near-burner coal flame phenomena. Fourth Int. Conf. on Technoi. and Combust, for a Clean Environ.. Lisbon, Portugal. Calouste Gulbenkian Foundation. Niksa, S., Cho, S. (1998), Twenty-Seventh Int. Symp on Combust, Combustion Institute, Pittsburgh, pp 2905- 2913, Nunn, T. R., J. B. Howard, et al. (1985) Product compositions and kinetics in the rapid pyrolysis of milled wood lignm. Ind. Engr. Chem. Process Des and Develop.. Vol. 24, pp. 844-852. Pindoria. R. V., J.-Y. Lim, et al. (1997). Structural characterization of biomass pyrolysis tars/oils from eucalyptus wood waste: effect of H2 pressure and sample configuration. Fuel, Vol. 76(11), pp. 1013-1023 Raveendran, K., A. Ganesh, et al. (1995). influence of mineral matter on biomass pyrolysis charactenstics Fuel Vol. 74(12), pp. 1812-1822. Xu, W. C, Tomita, A. (1989), Fuel. Vol. 66. p. 627 |