The Use of Nonlinearity Measures in the Estimation of Kinetic Parameters of Sugarcane Bagasse Pyrolysis

• Published in: Chemical engineering & technology Vol. 33; no. 10; pp. 1699 - 1705
• Main Authors: Lira, T. S., Santos, K. G., Murata, V. V., Gianesella, M., Barrozo, M. A. S.
• Format: Journal Article
• Language: English
• Published: Weinheim WILEY-VCH Verlag 01.10.2010; WILEY‐VCH Verlag; Wiley-VCH
• Subjects: Applied sciences; Chemical engineering; Exact sciences and technology; Kinetics; Nonlinearity measures; Pyrolysis; Sugarcane bagasse; Kinetic model; Pyrolysis; Parameter estimation; Parallel reaction; Bias; Non linear model; Prediction; Nonlinearity; Biomass; Kinetic parameter; Modeling
• ISSN: 0930-7516; 1521-4125
• DOI: 10.1002/ceat.201000137

The majority of the pyrolysis kinetics models presented in the literature is nonlinear. In these models, the influence of temperature is normally described by the Arrhenius equation. In some studies related to parameter estimation of nonlinear models suggestions can be found for reparameterization of the Arrhenius‐type equation due to inadequate results on the parameter estimation. In this work, kinetic modeling is proposed in order to predict the primary biomass decomposition behavior under a dynamic regime. This model is based on the traditional model of parallel reactions and uses the Arrhenius‐type equation in the reparameterized form. Some nonlinearity measures are used as a tool to correctly estimate the kinetic parameters of the pyrolysis of sugarcane bagasse. The predictions from the proposed model properly reproduced the experimental DTG curves. The reparametrized model showed non‐significance for bias and nonlinearity measures. Some procedures are used to validate the statistical properties of the least‐squares estimators of nonlinear models. This study focuses on the use of nonlinearity measures in the estimation of kinetic parameters of sugarcane bagasse pyrolysis. A reparametrized model is proposed in order to predict the primary biomass decomposition behavior under dynamic regime.