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Thermogravimetric study of biomass pyrolysis kinetics. A distributed activation energy model with prediction tests

By: Publication details: ene./feb. 2011Description: 9 p. ; 24-32 In: Energy & fuels 25Summary: Transcripción del resumen del autor. The pyrolysis of four biomasses (corn stalk, rice husk, sorghum straw, and wheat straw) was studied at different temperature-time functions in an inert gas flow by thermogravimetric analysis (TGA). Linear and stepwise heating programs were employed. A distributed activation energy model (DAEM) with three pools of reactants (three pseudocomponents) was used because of the complexity of the biomass samples of agricultural origin. Compensation effects were observed between the kinetic parameters as in the works of other investigators. The compensation effects result in ambiguous parameter values; hence, they were eliminated with a decrease in the number of unknown parameters. For this purpose, some of the kinetic parameters were assumed to be the same for the four biomasses. This approach also helps to express the similarities of the samples in the model. The 16 experiments were evaluated simultaneously by the method of least squares, yielding dependable kinetic parameters. The resulting models describe well the experimental data and are suitable for predicting experiments at higher heating rates. The checks on the prediction capabilities were considered to be an essential part of the model verification.
Item type: Artículo de Revista
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Biblioteca Alejandro Angel Bulgheroni Not for loan 200052377

Transcripción del resumen del autor. The pyrolysis of four biomasses (corn stalk, rice husk, sorghum straw, and wheat straw) was studied at different temperature-time functions in an inert gas flow by thermogravimetric analysis (TGA). Linear and stepwise heating programs were employed. A distributed activation energy model (DAEM) with three pools of reactants (three pseudocomponents) was used because of the complexity of the biomass samples of agricultural origin. Compensation effects were observed between the kinetic parameters as in the works of other investigators. The compensation effects result in ambiguous parameter values; hence, they were eliminated with a decrease in the number of unknown parameters. For this purpose, some of the kinetic parameters were assumed to be the same for the four biomasses. This approach also helps to express the similarities of the samples in the model. The 16 experiments were evaluated simultaneously by the method of least squares, yielding dependable kinetic parameters. The resulting models describe well the experimental data and are suitable for predicting experiments at higher heating rates. The checks on the prediction capabilities were considered to be an essential part of the model verification.

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