Semi Analytical Solution of a Heat Transfer and Kinetic Models Applied in a Biomass Pyrolysis Reactor

摘要

Currently, fuels renewal and innovation has been intensively investigated by scientific community. Nevertheless, thermal cracking (pyrolysis) is considered a promising technique in biofuels production. This paper proposes a semi analytical solution of a mathematical model for heat transfer and chemical conversion phenomena applied to a biomass pyrolysis reactor. Equations set were solved through the Finite Analytical Method. Thus, it was possible to incorporate the non-linear terms in the solution and develop a numerical procedure in which time interval can be made arbitrarily small without stability and convergence problems. The thermochemical process is a decomposition reaction (reduction) occurring at higher temperatures, in an environment quasi or deoxygenated – a rupture of the original molecular structure of a given compound or mixture by heating. This is self-sustaining from an energy standpoint, since the ‘break’ in a waste processing reactor produces surplus energy. The biomass pyrolysis reactor was simulated, based on works of heat and mass transfer models and solved by Walas [1959] and modified by Leung et al. [1965] and also in the studies of Bertoli [2000], Meier et al. [2009] and Wiggers et al. [2009]. Steady-state, uniform average temperature, adiabatic reactor, inert particles, first-order reactions were the simplifying hypothesis of the mathematical model. The semi analytical solution was realized considering the nonlinearity of the equations system by partitioning the reactor in finite intervals; the linear terms remains and the non-linear are made constant in the intervals. Finite Analytical Method is based on the numerical solution incorporating a local solution of the partial or ordinary differential equations. For data comparison (semi analytical versus numerical solutions) Runge-Kutta-Fehlberg routine was used. The proposed method was successfully applied and the results between semi analytical and numerical solutions agree with minimum error values.