Modeling the thermochemical degradation of biomass inside a fast pyrolysis fluidized bed reactor

Abstract

A fast pyrolysis process in a bubbling fluidized bed has been modeled, thoroughly reproduced and scrutinized with the help of a combined Eulerian/Lagrangian simulation method. The 3-D model is compared to experimental results from a 100 g/h bubbling fluidized bed pyrolyzer including such variables as particle composition at the outlet and gas/vapor/water yields as a function of fluidization conditions, biomass moisture concentrations, and bed temperatures. Multiprocessor simulations on a high-end computer have been carried out to enable the tracking of each of the 0.8 million individual discrete sand and biomass particles, making it possible to look at accurate and detailed multiscale information (i.e., any desired particle property, trajectory, particle interaction) over the entire particle life time. The overall thermochemical degradation process of biomass is influenced by local flow and particle properties and, therefore, accurate and detailed modeling reveals unprecedented insight into such complex processes. It has been found, that the superficial fluidization velocity is important while the particle moisture content is less significant for the final bio-oil yield

Multi-fluid reactive modeling of fluidized bed pyrolysis process

“…The effect of fluidization velocity, temperature and moisture content on product yield and composition was analyzed and compared with experimental results. However, most of these studies (Bruchmüller et al, 2012;Papadikis et al, 2009) were carried out for considerably less amount of time not sufficient for approaching the steady state inside the reactor. Furthermore, the lumped reaction model for biomass decomposition and tar cracking needs to be studied during biomass pyrolysis in the large scale reactors.…”

“…The results for apparent biomass density, vertical velocity, average temperature and product yields were also compared for different 2-D grid sizes and between 2-D and 3-D domain along with experimental data (Xue et al, 2012). Bruchmüller et al (2012) studied the thermo-chemical decomposition of biomass using Computational Fluid Dynamics-Discrete Element Model (CFD-DEM) approach. The effect of fluidization velocity, temperature and moisture content on product yield and composition was analyzed and compared with experimental results.…”

A numerical study on biomass fast pyrolysis process: A comparison between full lumped modeling and hybrid modeling combined with CFD

“…Therefore, many experimental studies have been conducted to determine the optimum conditions to obtain oil of higher yield and good quality (Bok et al, 2012(Bok et al, , 2013Choi et al, 2012;Ellens and Brown, 2012;Kim et al, 2014;Salehi et al, 2011;Wilson et al, 2013). For numerical studies, basic studies using computational fluid dynamics (hereinafter abbreviated as CFD) were carried out for the fast pyrolysis of biomass (Boateng and Mtui, 2012;Bruchmuller et al, 2012;Choi et al, 2009;Choi, 2011;Mellin et al, 2013;Papadikis et al, 2009a,b,c;Xiong et al, 2013aXiong et al, ,b, 2014Xue et al, 2011Xue et al, , 2012. Although lumped model study on mass analysis of fast pyrolysis is common, investigations on process analysis (using lumped model) is rare (Wright et al, 2010).…”

Numerical simulation of biomass fast pyrolysis in an auger reactor

“…For biomass fast pyrolysis simulation, CFD has been applied mainly to the fluidized-bed reactor because of the simple geometry and widespread applications of this reactor [26][27][28][29][30][31][32][33][34][35][36]. Fluidized beds can provide excellent gas-solid mixing and heat transfer.…”