Numerical simulations on the effect of potassium on the biomass fast pyrolysis in fluidized bed reactor

Abstract In this study, the effect of potassium on the cellulose fast pyrolysis in a fluidized bed reactor has been studied using Computational Fluid Dynamics (CFD). A multiphase pyrolysis model of cellulose has been implemented by integrating the hydrodynamics of the fluidized bed with an adjusted cellulose pyrolysis mechanism that accounts for the effect of potassium. The model has been validated with the reported experimental data. The simulation results show that potassium concentration and reactor temperature have a significant effect on the yield and component of cellulose pyrolysis products. The product yields fluctuate is caused by the unstable flow in the fluidized bed. The result shows that the increased potassium concentration in the cellulose causes a significant increase of the gas and char yields and reduction in the bio-oil. Also, the dramatic composition variations in bio-oil and gas were observed due to the inhibition of fragmentation, and the depolymerization reaction of activated cellulose, and the catalysis of the depolymerization reaction of cellulose. It is also found that the increase in reactor temperature greatly enhances the endothermic pyrolysis reaction, which leads to the significant changes in the yield and composition of cellulose pyrolysis products.

[1]  Vishnu Pareek,et al.  Multi-fluid reactive modeling of fluidized bed pyrolysis process , 2015 .

[2]  P. Mtui,et al.  CFD modeling of space-time evolution of fast pyrolysis products in a bench-scale fluidized-bed reactor , 2012 .

[3]  Ger Devlin,et al.  A review of recent laboratory research and commercial developments in fast pyrolysis and upgrading , 2011 .

[4]  Manisha Patel Pyrolysis and gasification of biomass and acid hydrolysis residues , 2013 .

[5]  P. Rutkowski Pyrolysis of cellulose, xylan and lignin with the K 2CO 3 and ZnCl 2 addition for bio-oil production , 2011 .

[6]  Song-Charng Kong,et al.  Development of a generalized numerical framework for simulating biomass fast pyrolysis in fluidize , 2013 .

[7]  A. Bridgwater,et al.  Lignin fast pyrolysis: results from an international collaboration. , 2010 .

[8]  Kai H. Luo,et al.  Modeling the thermochemical degradation of biomass inside a fast pyrolysis fluidized bed reactor , 2012 .

[9]  D. Gidaspow,et al.  Hydrodynamics of circulating fluidized beds: Kinetic theory approach , 1991 .

[10]  Vishnu Pareek,et al.  CFD modeling of mixing/segregation behavior of biomass and biochar particles in a bubbling fluidized bed , 2014 .

[11]  Michael A. Serio,et al.  TG-FTIR Study of the Influence of potassium Chloride on Wheat Straw Pyrolysis , 1998 .

[12]  A. Galgano,et al.  Influences of the Chemical State of Alkaline Compounds and the Nature of Alkali Metal on Wood Pyrolysis , 2009 .

[13]  B. G. M. van Wachem,et al.  Tar formation variations during fluidised bed pyrolytic biomass conversion , 2013 .

[14]  S. Saka,et al.  Different action of alkali/alkaline earth metal chlorides on cellulose pyrolysis , 2008 .

[15]  Theodore J. Heindel,et al.  A CFD model for biomass fast pyrolysis in fluidized-bed reactors , 2010 .

[16]  Weihong Yang,et al.  Computational fluid dynamics modeling of biomass fast pyrolysis in a fluidized bed reactor, using a comprehensive chemistry scheme , 2014 .

[17]  J. Satrio,et al.  Influence of inorganic salts on the primary pyrolysis products of cellulose. , 2010, Bioresource technology.

[18]  I. Choi,et al.  Fast pyrolysis of potassium impregnated poplar wood and characterization of its influence on the formation as well as properties of pyrolytic products. , 2013, Bioresource technology.

[19]  Yi Wang,et al.  Effects of inherent alkali and alkaline earth metallic species on biomass pyrolysis at different temperatures. , 2015, Bioresource technology.

[20]  R. Fox,et al.  Experimental validation and CFD modeling study of biomass fast pyrolysis in fluidized-bed reactors , 2012 .

[21]  S. Gu,et al.  Computational fluid dynamics modelling of biomass fast pyrolysis in fluidised bed reactors, focusing different kinetic schemes. , 2016, Bioresource technology.

[22]  Flavio Manenti,et al.  Kinetic modeling of the thermal degradation and combustion of biomass , 2014 .

[23]  Robert J. Braun,et al.  Evaluating the effect of potassium on cellulose pyrolysis reaction kinetics , 2015 .

[24]  An Euler–Euler approach to modeling biomass fast pyrolysis in fluidized-bed reactors – Focusing on the gas phase , 2013 .

[25]  Manuel Garcia-Perez,et al.  Mallee wood fast pyrolysis: Effects of alkali and alkaline earth metallic species on the yield and composition of bio-oil , 2011 .

[26]  A. Bridgwater,et al.  Application of CFD to model fast pyrolysis of biomass , 2009 .

[27]  Weiping Song,et al.  Bioenergy and biofuels: History, status, and perspective , 2015 .

[28]  S. Kong,et al.  Modeling Effects of Operating Conditions on Biomass Fast Pyrolysis in Bubbling Fluidized Bed Reactors , 2013 .

[29]  D. Vamvuka,et al.  Bio‐oil, solid and gaseous biofuels from biomass pyrolysis processes—An overview , 2011 .

[30]  A. Bridgwater,et al.  Overview of Applications of Biomass Fast Pyrolysis Oil , 2004 .

[31]  A. Bridgwater Review of fast pyrolysis of biomass and product upgrading , 2012 .

[32]  D. Gunn Transfer of heat or mass to particles in fixed and fluidised beds , 1978 .

[33]  Sai Gu,et al.  CFD modelling of the fast pyrolysis of biomass in fluidised bed reactors. Part B: Heat, momentum and mass transport in bubbling fluidised beds , 2009 .

[34]  Mohd Ambar Yarmo,et al.  A review on bio-oil production from biomass by using pyrolysis method , 2012 .